Nagendra Tripurana

RESILIENCE DRILL

Fail a zone, or a region. Watch it hold.

Simulated resilience drill · not live telemetry

In a regulated bank, availability isn't a claim — it's a rehearsal you can produce evidence for. One drill, two separate engineering concerns. High availability asks whether the service stays up when a single Availability Zone fails. Disaster recovery asks whether the platform and its data can be recovered when the whole primary region is no longer enough. Run either scenario and watch both answer.

Simulation elapsed00:00

Conceptual resilience model — implementation varies by database platform. Availability Zones protect against zone-level failure inside the primary region; a secondary region protects against region-level failure. Failover is not recovery until the application is validated. The elapsed counter is animation time, not a recovery-time objective.

01 DetectHA

02 FailoverHA

03 App validateHA

04 DR validateDR

05 Restore testDR

06 EvidenceDR

Two separate concerns. On the left, high availability across three Availability Zones in the primary Azure region keeps the service up through a zone-level failure — and is not finished until the application itself is validated; not every database technology necessarily replicates into all three zones the same way. On the right, disaster-recovery readiness in a secondary region: an asynchronous geo-replica, a restoration-test target, and a recovery estate fed out of band, deliberately outside the write path. Conceptual model — implementation varies by database platform. Simulated drill, not live telemetry.

resilience log idle

application validation post-failover

Connectivitypending

Read pathpending

Write pathpending

Data consistencypending

✓ Resilience drill reportevidence recorded

HA · Service availability

Primary-zone failure detected.
HA replica promoted.
Writer endpoint restored.
Application connectivity validated.
Read/write paths validated.
Data consistency validated.
Application healthy.
Service recovery validated within the defined RTO target.

DR · Recovery readiness

Secondary-region geo-replica health validated.
Replication state checked against the defined RPO target.
Backup and recovery controls validated.
Restoration test passed.
Recoverability validated.
Evidence captured.

✓ Resilience drill complete
HA recovery validated · DR readiness validated · Evidence captured

Corrective actions can be tracked through the post-incident review process.

01 / ARCHITECT

Three platforms, one foundation

Platform architecture ↓ select a layer

I lead cloud database and data-platform engineering across three regulated Wio platforms — Bank, Invest and Lending — on a shared foundation built around resilience, security, observability and governance.

Platform 01

Wio Bank

Core banking database and data-platform engineering, designed around high availability, zone/geo resilience and defined RPO/RTO objectives.

Databases
Data platform
BI & reporting
HA / DR

Platform 02

Wio Invest / Securities

Data-platform and database engineering supporting investment and trading workloads, with security, encryption, traceability and operational resilience built into the platform.

Databases
Data platform
Security
Resilience

Platform 03

Wio Lending

Database and data services supporting lending workloads within the same governed platform foundation, with security, observability, resilience and audit readiness.

Databases
Data platform
Governance
Audit readiness

The platform estate across Bank, Invest and Lending. All three products draw on the same six-layer foundation; the dashed spine on the right marks the three concerns that apply to every layer rather than sitting inside one.

02 / BUILD

Data Platform Engineering & AI Infrastructure

Streaming · Lakehouse · GenAI

The systems that move, process and govern the bank's data — from real-time event streaming and enterprise data pipelines through lakehouse analytics, highly available data stores and privately governed GenAI infrastructure.

01 Real-time streaming

Move events

Scalable event-streaming platforms supporting business-critical workloads, with partitioning, throughput optimisation, observability and governed deployment through CI/CD.

Apache Kafka and Azure Event Hubs supporting event-driven workloads
Debezium connectors on Kafka Connect streaming change data capture off the operational databases
Partitioning, throughput and operational tuning at cluster level
Kafka deployment and configuration governed through Azure DevOps pipelines

Apache KafkaKafka ConnectDebezium CDCAzure Event HubsOffset Explorer

02 Lakehouse & big data

Process at scale

Enterprise data-processing engineered on Azure Databricks for scalable processing, performance, governance and workload optimisation — a single lakehouse consolidated from two earlier estates.

Azure Databricks cluster provisioning, tuning and workload optimisation
HDInsight and Azure Synapse estates established, then consolidated onto Databricks
Unity Catalog for access control, governance and data-platform standards

Azure DatabricksApache SparkPySparkUnity CatalogAzure Data LakeHadoop

03 Data pipelines & BI

Transform and serve

ETL/ELT pipelines built across Azure Data Factory and Databricks, transforming enterprise data into governed datasets for analytics, reporting and business decision-making.

Azure Data Factory, Databricks and Apache Airflow orchestrating pipelines across multiple source systems
PySpark and Spark SQL for transformation and processing
Analytics and reporting delivered through Power BI, Tableau and related platforms

Azure Data FactoryApache AirflowDatabricksPySparkSpark SQLPower BITableauMetabase

04 GenAI & RAG infrastructure

Enable intelligent workloads

Secure GenAI and retrieval-augmented generation infrastructure designed around private connectivity, self-hosted models, vector search and governed access controls.

Azure AI Foundry and governed access to hosted AI capabilities
Self-hosted Qwen and Ollama model infrastructure
Qdrant vector database supporting embeddings, retrieval and semantic search
Private networking and security controls for enterprise AI workloads

Azure AI FoundryQwenOllamaQdrantRAGVector searchPerplexity

05 Resilient data stores

Protect operational data

Highly available relational and non-relational data platforms engineered with zone and geo-resilience, backup and recovery strategies, and clearly defined RPO/RTO objectives.

HA architectures across SQL Server, PostgreSQL, MySQL and MongoDB Atlas
Zone and geo-resilience aligned with business continuity requirements
Operational coverage across relational, document, caching and graph platforms

SQL ServerAzure SQL DBSQL MIPostgreSQLMySQLMongoDB AtlasRedisNeo4j

06 Data platform governance & operations

Govern and operate the platform

Operational governance embedded across the data platform through access control, catalogue and lineage, observability, deployment standards and cost management.

Unity Catalog and Microsoft Purview supporting access governance, catalogue and lineage
Monitoring and observability across data-platform workloads
CI/CD and infrastructure automation supporting controlled platform changes
Performance and cost optimisation across processing workloads

Unity CatalogMicrosoft PurviewAzure MonitorGrafanaAzure DevOpsTerraformFinOps

03 / MIGRATE

Run a migration cutover

Interactive · cutover console

Six programmes where the estate materially changed shape. A migration isn't the copy — it's the plan around it: pre-checks, replication in sync, a cutover window with a backout point still open, validation, then sign-off with the evidence recorded. Pick one and run it.

cutover console

Source

Azure Cosmos DB

document data store · platform-bound model

Target

MongoDB Atlas

highly available cluster · geo-replication · defined RPO / RTO

Pre-checkscompatibility, dependencies, capacity

Replicationinitial load, change capture in sync

Cutovertraffic switched to targetbackout point

Validationdata and performance verified

Sign-offgovernance and audit evidence recorded

Outcome Led the end-to-end migration and modernisation from Cosmos DB to MongoDB Atlas — Change Stream-based synchronization, validated cutover, and a highly available cluster architecture with defined RPO/RTO.

04 / AUTOMATE

DevOps, CI/CD & orchestration

Terraform · Terragrunt · Argo CD · Azure DevOps · n8n

Automation applied across infrastructure provisioning, platform configuration, release workflows, data movement and operational tasks — using version-controlled, repeatable workflows with approval, validation and rollback controls.

IaC Infrastructure as Code + GitOps

Infrastructure provisioning standardised through reusable Terraform modules, with Terragrunt coordinating environment-specific configuration. Kubernetes/AKS platform and workload configuration is reconciled through Argo CD using Git as the desired-state source.

Reusable Terraform modules with Terragrunt for environment orchestration
Argo CD reconciliation for Kubernetes/AKS platform and workload configuration
Git-based change history, peer review and controlled promotion
Repeatable environment builds with configuration drift reduced through declarative infrastructure
ARM templates retained where required for Azure-specific deployments

TerraformTerragruntArgo CDAzure DevOpsAKSGitOpsARM Templates

CI/CD Pipelines & release engineering

CI/CD pipelines supporting controlled application and platform releases across development, QA and production environments, with deployment traceability and environment-specific governance.

Azure DevOps pipelines with GitHub and Azure Repos source control
Build, deployment and environment promotion workflows
Approval gates and controlled production releases
Deployment validation and rollback procedures
Secrets and configuration referenced through approved platform controls
Kafka and platform configuration delivered through governed deployment pipelines where applicable

Azure DevOpsGitHubAzure ReposDockerKubernetesCI/CD

ORCH Workflow & data orchestration

Operational and data workflows orchestrated across cloud, database and platform services, reducing repetitive manual execution while preserving monitoring, failure handling and operational control.

n8n workflows integrating AI, cloud and database services
Apache Airflow for scheduled and dependency-driven data workflows
Azure Logic Apps for event and integration workflows
Oozie and YARN used across earlier Hadoop-based data platforms
Workflow execution monitored with failure handling and operational visibility

n8nAirflowAzure Logic AppsOozieYARN

RUN Reliability, incident & change management

Operational controls spanning monitoring, incident response, production change, recovery and post-incident improvement across database and cloud platforms.

On-call support across database and platform services
Alert triage using service health, logs, metrics and dependency signals
Incident severity assessment, escalation and cross-team coordination
Production changes executed through approval, validation and rollback controls
Post-incident reviews with root-cause analysis and corrective actions tracked to closure
Backup and recovery operations validated through restoration testing
Monitoring and observability across Azure Monitor, Datadog, Dynatrace, Grafana and Kibana

On-callIncident ManagementProblem ManagementChange ManagementAzure MonitorDynatraceDatadogGrafanaServiceNowJIRA

05 / GOVERN

Open the evidence pack

Interactive · audit evidence

I participate directly in internal, external and regulatory audits and data privacy assessments — providing technical evidence, control walkthroughs and engineering clarification. Select a control to see how it is implemented and what evidence it produces.

Pack reviewed 1 / 8

Encryption & key management CTRL-01

06 / OPTIMIZE

FinOps & cost governance

Budget · Transparency · Efficiency

Cloud and data-platform spend managed as an engineering discipline — combining workload demand, capacity, utilisation and service economics with budget governance, cost visibility and executive reporting.

01 Budget & FinOps governance

Technology spend governed through budget planning, cost visibility and workload-level accountability, connecting platform consumption and capacity decisions to business priorities.

IT budget planning, forecasting and spend tracking
Budget-versus-actual variance reviewed against platform demand
Cloud cost visibility across database, compute, storage and data platforms
Cost allocation and ownership through resource organisation and tagging where applicable
Executive-level reporting covering spend, capacity and optimisation opportunities
Architecture and procurement decisions evaluated against operational and financial impact

02 Workload & capacity efficiency

Database and data-platform capacity continuously evaluated against workload behaviour, performance requirements and service cost — rightsizing resources without compromising availability or recovery objectives.

Database compute and storage rightsizing using utilisation and workload telemetry
Databricks cluster sizing and workload optimisation
PostgreSQL, SQL Server, MongoDB and Redis capacity optimisation where applicable
Storage growth, retention and data lifecycle reviewed as cost drivers
Idle and over-provisioned capacity identified through monitoring
Scaling decisions validated against performance, HA and recovery requirements

03 Cost optimisation engineering

Cost optimisation applied across architecture, capacity and data lifecycle — reducing unnecessary consumption while preserving performance, resilience and operational headroom.

Compute and database SKU rightsizing based on observed utilisation
Reserved capacity / commitment options evaluated for predictable workloads where applicable
Storage lifecycle, archival and retention used to control long-term data growth
Scaling and architecture decisions reviewed against workload demand
Monitoring and cost telemetry used to identify optimisation opportunities
Savings validated against service performance and reliability requirements

04 Performance economics

Performance tuning treated as part of capacity engineering — improving workload efficiency before adding infrastructure.

SQL execution plans and workload behaviour analysed before compute scaling
Oracle AWR, ASH and ADDM used for performance diagnosis where applicable
Query and index optimisation used to reduce unnecessary database resource consumption
Connection, memory and I/O behaviour considered during capacity decisions
Performance baselines used to validate infrastructure changes

AWRASHADDMQuery TuningIndexingCapacityFinOps

07 / LEAD

Leadership & technology strategy

Team of 6 · CTO reporting line

Reporting to the Chief Technology Officer, leading a team of six across database, cloud and data-platform engineering — accountable for technical standards, platform delivery, operational resilience, engineering governance and capability development, with direct participation in internal and regulatory audit engagements.

TEAM Engineering leadership

Lead and mentor a six-person engineering team across database, cloud and data-platform disciplines
Define roles and participate in technical hiring and engineering assessments
Set objectives, review performance and support career development
Establish technical ownership and accountability across platform services
Review designs, implementation approaches and production-readiness requirements
Develop engineering capability through mentoring, knowledge sharing and technical reviews
Coordinate delivery across Platform, Security, Network, Data and Application teams

STRAT Architecture, strategy & standards

Define database and data-platform engineering standards
Establish reference architectures and reusable technology patterns
Review technology choices against scalability, resilience, security, operability and cost
Drive platform modernisation and cloud migration roadmaps
Translate business requirements into technical architecture and platform capability
Define lifecycle and modernisation priorities for database and data-platform technologies
Communicate architecture decisions, technical risks and investment priorities to senior stakeholders

GOV Engineering governance

Architecture and design reviews across database and data-platform changes
Production changes governed through approval, validation and rollback controls
Cloud migration programmes delivered through structured technical governance
Platform standards aligned with security, audit and regulatory requirements
Operational readiness reviewed across monitoring, backup, HA, DR and supportability
Technical risks, dependencies and exceptions tracked through delivery
Technical evidence prepared and presented during audit and control reviews
Audit observations and remediation actions tracked through technical closure

RISK Resilience & technology risk

HA and DR architectures designed around workload criticality and failure domains
RPO and RTO requirements translated into platform recovery designs
Replication health, failover readiness and recovery capability periodically validated
DR exercises used to verify recovery procedures and identify gaps
Capacity, availability and operational risks reviewed before significant production changes
Monitoring and alerting used for proactive risk identification
Corrective actions tracked following incidents, recovery tests and technical reviews

AUDIT Audit & technical assurance

Directly support internal, external and regulatory audits by translating database, cloud and data-platform controls into verifiable technical evidence and responding to auditor observations and technical queries.

Participate directly in internal, external and regulatory audit engagements
Provide technical evidence across database, cloud and data-platform controls
Explain architecture, security, access, backup, recovery and operational controls during audit walkthroughs
Coordinate evidence collection across Engineering, Security, Risk and Compliance teams
Validate evidence for completeness, traceability and technical accuracy
Respond to technical audit queries and control walkthroughs
Track audit observations, remediation actions and closure evidence
Maintain technical audit readiness across platform services

PLAT Platform ownership

Technical ownership across database and data-platform services
Platform lifecycle spanning design, build, migration, operation and modernisation
Capacity, availability, security and cost managed as connected engineering concerns
Production standards established for monitoring, backup, HA/DR and operational readiness
Technology lifecycle and technical-debt priorities managed through engineering roadmaps
Cross-team dependencies coordinated for major platform changes

CAREER

Sixteen years, four organisations

Select a role to expand

Sixteen years across enterprise database engineering, high availability, cloud migration and data-platform modernisation — progressing from large-scale on-premises operations to leading cloud, DevOps and data-platform engineering for a digital bank. Experience spans IBM enterprise environments, healthcare platforms at Optum, large-scale infrastructure transformation at Al-Futtaim, and cloud-native banking platforms at Wio Bank.

Report to the CTO and lead a six-person engineering team across database, cloud and data-platform disciplines, covering technical direction, platform delivery, engineering standards, mentoring and operational accountability.
Design and operate cloud database and data-platform architectures across Azure and Alibaba Cloud, covering SQL Server, PostgreSQL, MySQL, MongoDB Atlas, Redis, Databricks and Kafka.
Engineer high-availability and disaster-recovery architectures using platform-appropriate replication, failover and recovery mechanisms, with RPO/RTO requirements translated into tested recovery designs.
Lead database and data-platform modernisation initiatives including Cosmos DB → MongoDB Atlas, HDInsight/Synapse → Databricks, PostgreSQL platform upgrades and enterprise database migration programmes.
Standardise infrastructure provisioning through Terraform and Terragrunt, with Kubernetes/AKS configuration delivered through Argo CD GitOps and governed CI/CD workflows.
Engineer and govern data-platform services spanning Databricks, Kafka and ETL/ELT workloads, with Unity Catalog supporting access governance and data-platform controls.
Implement database and platform security controls across encryption, access management, privileged access, audit logging and traceability, while participating directly in internal, external and regulatory audits through technical evidence and control walkthroughs.
Govern backup and recovery across database, VM, Kubernetes and storage workloads, with restoration testing and recovery validation used to verify recoverability rather than relying on backup-job success alone.
Drive database and data-platform FinOps through capacity planning, rightsizing, storage lifecycle management and workload optimisation, balancing cost against performance, resilience and growth requirements.
Contribute to secure GenAI and RAG platform infrastructure, integrating AI services, vector databases and self-hosted model components within private-networked and governed cloud environments.

AzureAlibaba CloudMongoDB AtlasSQL ServerPostgreSQLMySQLRedisDatabricksKafkaAKSTerraformTerragruntArgo CDAzure DevOpsUnity CatalogAzure AI FoundryQdrant

Supported enterprise database platforms across production and non-production environments with focus on availability, performance and recoverability.
Delivered on-premises data-centre to Microsoft Azure migration activities across database and infrastructure workloads.
Migrated and modernised SQL Server workloads across Azure VM, Azure SQL Database and Azure SQL Managed Instance targets where applicable.
Executed cross-platform Oracle RAC migration to Azure for financial and healthcare workloads, including MySQL PaaS and DB2 HADR configuration.
Used migration assessment and migration tooling to evaluate compatibility, dependencies and target architecture.
Used Distributed Availability Groups for low-downtime SQL Server migration scenarios and Azure Site Recovery for VM migration where applicable.
Performed migration cutover, application validation, performance verification and rollback planning.
Engineered SQL Server availability, backup/recovery and DR controls.
Supported database performance analysis, capacity planning and production incident resolution.
Participated in change, incident and problem-management processes across enterprise environments.

AzureSQL ServerOracle RACPostgreSQLDMSDistributed AGsASRDB2 HADR

Administered enterprise database environments supporting healthcare application workloads.
Supported on-premises database and application workload migration to Amazon Web Services.
Performed migration assessment, dependency analysis, target sizing, synchronization, cutover and post-migration validation.
Supported SQL Server, Oracle and PostgreSQL workloads across enterprise environments where applicable.
Applied database backup, recovery, availability, security and performance controls.
Supported production incidents, change activities and operational troubleshooting.
Worked within healthcare security and compliance requirements, including technical controls and audit evidence where applicable.

AWSAmazon EC2Amazon RDSSQL ServerOraclePostgreSQLSOXHIPAA

Administered enterprise Oracle, SQL Server, DB2 and MySQL environments across production and non-production estates.
Performed database installation, configuration, patching, upgrades, backup/recovery, performance tuning and capacity management.
Engineered Oracle high availability by migrating standalone database environments to Oracle RAC, implementing Grid Infrastructure and ASM.
Migrated DB2 standalone environments to DB2 HADR primary/standby architectures.
Improved MySQL availability by moving standalone VM-hosted databases to clustered / HA architectures.
Modernised SQL Server environments from failover clustering toward Always On Availability Groups where applicable.
Performed SQL Server version upgrades including SQL Server 2008/2008 R2 → SQL Server 2012 and later environments where applicable.
Supported replication, failover, recovery testing and production incident resolution.
Used database-native performance diagnostics and tuning techniques across enterprise workloads.
Worked within structured change, incident, problem and service-management processes.

Oracle RACGrid InfrastructureASMDB2 HADRMySQL HA ClusterAlways OnSQL ServerDB2

STACK

The working toolset

Select any technology

Sixteen years of accumulated surface area — filter by domain, then select anything to see where it sits in the record.

Cloud platforms

Network & platform security

Relational databases

Non-relational databases

Data platform, ETL & analytics

Streaming

DevOps & CI/CD

Automation & orchestration

Backup & recovery

AI, GenAI & vector infrastructure

Monitoring & observability

Languages & scripting

Database & development tooling

Operating systems & storage

Engineering tools & collaboration

DEPTH

Cloud & database expertise

Where the depth actually sits

Technology breadth is easy to list; operational depth is harder to demonstrate. This is the shape of mine — from enterprise database engineering and high availability through cloud migration, managed database platforms, data engineering and cloud-native operations.

The foundation is hands-on database engineering: installation, upgrades, clustering, replication, backup and recovery, performance tuning, migration, HA/DR and production operations. Cloud architecture was built on top of that foundation.

FoundationOn-premises database engineering

Built the first eight years of my career operating enterprise database estates across physical and virtualised infrastructure — installation, configuration, patching, upgrades, clustering, replication, performance tuning, backup/recovery and production incident management across heterogeneous UNIX, Linux and Windows environments. High-availability patterns included Oracle RAC and Data Guard, DB2 HADR, SQL Server failover clustering, Log Shipping and Database Mirroring, alongside SAN/NAS-backed enterprise storage.

Oracle RACData GuardRMANDB2 HADRSQL Server FCILog ShippingDatabase MirroringPITRAIXHP-UXSolarisLinuxWindowsSAN / NAS

HybridOn-premises & cloud together

Progressed from traditional data-centre operations into hybrid-cloud architecture, connecting enterprise database and application estates with cloud platforms while maintaining availability, security, migration and recovery requirements across both environments. Experience includes database migration, private cloud connectivity, replication-based transition patterns, application cutover, rollback design and post-migration validation.

Hybrid cloud architectureAzure VNetsExpressRoutePrivate networkingData-centre migrationDistributed Availability GroupsDMSASRCutover & rollbackHA / DR

Primary cloudMicrosoft Azure

Primary cloud platform for database, data-platform and infrastructure engineering — spanning architecture, migration, managed database services, networking, security, backup/recovery, observability, governance and cost optimisation. Hands-on delivery covers both IaaS and PaaS database architectures together with AKS, Databricks and enterprise data services.

Azure VMsVNets / ExpressRouteAKSAzure SQL DatabaseSQL Managed InstancePostgreSQL Flexible ServerAzure Database for MySQLDatabricksData FactorySynapseHDInsightEvent HubsKey VaultManaged IdentitiesRBACPIMAzure BackupAzure MonitorLog AnalyticsMicrosoft PurviewAzure AI Foundry

Second cloudAlibaba Cloud

Production multi-cloud exposure at Wio Bank, with Alibaba Cloud forming part of the wider infrastructure and disaster-recovery architecture alongside Microsoft Azure. Operational responsibilities include Hybrid Backup Recovery configuration, retention, encryption, recovery validation and restoration testing.

Alibaba CloudHybrid Backup RecoveryBackup & recoveryRecovery validationRetentionEncryptionMulti-cloud

Multi-cloud coverageAWS, GCP & OCI

Hands-on AWS migration experience includes moving on-premises database and application workloads to AWS during the Optum period, covering migration assessment, target architecture, data synchronisation, cutover and validation. Additional architecture and platform exposure spans GCP and OCI as part of broader multi-cloud design and technology evaluation.

AWSAmazon EC2Amazon RDSAWS DMSDynamoDBCloud migrationGCPOCIMulti-cloud architecture

Deepest engineSQL Server

Deepest continuous database-engineering experience, spanning SQL Server 2008/2008 R2 through modern SQL Server releases and Azure-managed SQL platforms. Experience covers installation and upgrades, failover clustering, Always On Availability Groups, Distributed Availability Groups, Log Shipping, Database Mirroring, backup/PITR, TDE, performance tuning and production operations, followed by migration and modernisation to SQL Server on Azure VMs, Azure SQL Database and SQL Managed Instance. Cloud migration work includes assessment, replication/synchronisation, controlled cutover, rollback planning and post-migration performance validation. DP-300 certified.

SQL ServerSQL Server on Azure VMsAzure SQL DatabaseSQL Managed InstanceFailover Cluster InstancesAlways On AGsDistributed AGsLog ShippingDatabase MirroringBackup / PITRTDEDMSDMAPerformance tuningSSIS / SSRS

Enterprise RDBMSOracle

Enterprise Oracle experience across IBM, Optum and Al-Futtaim, covering single-instance and RAC environments, Data Guard, RMAN backup/recovery, performance diagnostics, patching, upgrades and production operations. Earlier engineering work included migration from Oracle single-instance environments to RAC-based high-availability architectures. Performance and diagnostic tooling includes OEM, AWR, ASH and ADDM, with RMAN used for backup, restore and recovery operations. OCA 11g and OCP 12c certified.

OracleOracle RACGrid InfrastructureASMData GuardRMANOEMAWRASHADDMPerformance tuning

Open-source RDBMSPostgreSQL & MySQL

Production PostgreSQL and MySQL engineering spanning self-managed and managed-cloud deployments, with responsibilities across provisioning, upgrades, replication, high availability, backup/recovery, performance tuning, capacity management and migration. Current PostgreSQL experience includes Azure Database for PostgreSQL Flexible Server and highly available production architectures. Earlier MySQL experience includes standalone database administration and migration toward clustered/high-availability architectures, with later cloud-managed MySQL exposure.

PostgreSQLPostgreSQL Flexible ServerMySQLMySQL clusteringReplicationHABackup / PITRPerformance tuningCloud migration

Document databaseMongoDB Atlas

Production MongoDB Atlas engineering at Wio Bank, including migration from Azure Cosmos DB, cluster architecture, indexing, performance optimisation, backup/recovery, scaling, replication, change streams and operational troubleshooting. Designed and operated highly available Atlas deployments with defined recovery objectives, including cross-region resilience patterns and analytics-node workloads. Migration and operational work includes data synchronisation, cutover validation, index redesign, workload isolation and production performance analysis. MongoDB Certified DBA Associate.

MongoDB AtlasReplica setsShardingChange StreamsAnalytics NodesIndex optimisationPerformance tuningBackup / restoreMigration from Cosmos DBCompassStudio 3T

Non-relationalRedis, Cosmos DB, HBase & Neo4j

Operational experience across specialised data stores used for caching, document, graph and distributed-data workloads. Redis supports high-throughput caching workloads in the current banking platform; Cosmos DB formed part of the earlier Azure estate before migration to MongoDB Atlas; HBase was operated alongside Hadoop-based data platforms; Neo4j forms part of the broader graph-data technology exposure.

RedisAzure Cosmos DBHBaseNeo4jCachingDocument databasesGraph databases

Legacy & specialistDB2, Sybase, Hive & YugabyteDB

Enterprise DB2 experience includes administration, backup/recovery, performance management and high-availability engineering, including migration from standalone DB2 environments to HADR primary/standby architectures. Earlier enterprise operations also included Sybase, while Hive and YugabyteDB form part of the wider data-platform and distributed-database technology coverage.

DB2DB2 HADRSybaseHiveYugabyteDBHA / DRBackup & recovery

Data platformDatabricks, Kafka & data engineering

Data-platform engineering spanning Databricks, Kafka and Azure data services, including platform deployment, workload migration, ETL/ELT orchestration, access governance, performance optimisation and production operations. Experience includes migration from HDInsight/Synapse-era workloads toward Databricks-based architectures, Kafka platform engineering on Kubernetes/AKS, and governance through Unity Catalog.

DatabricksApache SparkKafkaStrimziAKSData FactoryUnity CatalogETL / ELTHDInsightSynapse

CREDENTIALS

Certifications

11 credentials · 4 issuers

Credentials spanning cloud architecture, infrastructure, DevOps, security, database engineering and data management — aligned with the platforms and engineering disciplines used throughout my career.

Microsoft Azure 07

AZ-303Microsoft Azure Architect TechnologiesRetired · architecture path
AZ-304Microsoft Azure Architect DesignRetired · architecture path
AZ-400Designing and Implementing Microsoft DevOps Solutions
AZ-500Microsoft Azure Security Technologies
AZ-104Microsoft Azure Administrator
AZ-900Microsoft Azure Fundamentals
DP-300Administering Microsoft Azure SQL Solutions

Oracle 02

OCP 12cOracle Database 12c — Oracle Certified Professional
OCA 11gOracle Database 11g — Oracle Certified Associate

MongoDB 01

DBA AssociateMongoDB Certified DBA Associate

DAMA 01

CDMP AssociateCertified Data Management Professional — AssociateData Management Fundamentals

OPTIONAL

Query the profile

For the technically curious

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CONTACT

Let's talk platforms

Dubai, UAE · Golden Visa

Open to senior engineering and technology leadership roles, as well as consulting and advisory engagements, across cloud, database, DevOps and data platforms — particularly within regulated environments where architecture, resilience, security, governance, FinOps and operational reliability must be engineered together.

Emailnagendra.tripurana25@gmail.com Phone+971 52 374 8809 LinkedInnagendra-naveen-kumar-tripurana ↗

LocationDubai, UAE · UAE Golden Visa holder

EducationB.Tech, JNTU Kakinada — 2009