Database E2E Analyst, Officer

The Database Analyst will support the day-to-day operation, stability, and readiness of end-to-end QA environments used to validate application releases, patches, hotfixes, integration workflows, automation runs, and client-like testing scenarios.  The role requires hands-on ownership of database and cache readiness across Microsoft SQL Server, Oracle, Postgres, Cosmos DB, Snowflake, RocksDB, and Redis, with a strong emphasis on reliable test data, environment consistency, rapid troubleshooting and clear coordination with QA, Development, Release Management, and Platform teams.  They will ensure environments are available, correctly configured, appropriately seeded, validated after deployments, and recoverable when test cycles encounter data, schema, connectivity, or cache-state issues.  This candidate will also be a key contributor towards defining, deploying, and governing the unified data platform in the end-to-end QA environment.

Provide daily operational support for end-to-end QA, integration, patch, hotfix, release candidate, smoke test, automation, and client-like non-production environments. Monitor database and cache readiness before, during, and after deployments, including validating connectivity, data availability, schema compatibility, permissions, job completion, and environment-specific configuration. Serve as the primary database analyst for end-to-end environment related issues, triaging incidents, identifying root cause, coordinating fixes, and communicating status to stakeholders. Support repeatable setup, teardown, refresh, and re-seeding activities so QA teams may execute tests against predictable and consistent baselines. Maintain environment parity across supported QA and end-to-end landscapes, identifying drift in schemas, configuration, reference data, security grants, or cache state. Define and own the unified data platform for QA including architecture, governance, component reusability, synthetic data generation, data shape simulation, and data readiness. Enable self-service data capabilities across the broader end-to-end platform supporting the overall autonomous data provisioning for QA automation. Design and scale reusable test data services for workflow-driven automation by building data components, data profiles, synthetic data generation, and autonomous provisioning capabilities across UAP. Partner with pillar teams to enable data-aware, environment-independent workflow execution while ensuring data quality, security, governance, and CI/CD integration at enterprise scale Technical Environment / Qualifications Required: Minimum 09 years of experience as a Database Analyst. Hands-on experience support database environments in QA, UAT, integration staging and other non-production settings Strong SQL skills including joins, data validation queries, data comparison, troubleshooting and ad hoc analysis Practical experience with at least two of the following platforms: SQL Server, Oracle, Postgres, Cosmos DB, Snowflake, RocksDB, or Redis; willingness to learn the remaining platforms. Ability to analyze data-flow issues across upstream and downstream systems, including batch jobs, workflow execution, and integration services. Familiarity with cloud-hosted environments, Azure services, Kubernetes-based deployments, data pipelines, or workflow orchestration tools. Proven ability to design and execute data-driven and workflow-driven automation test scenarios Exposure to synthetic test data generation techniques (e.g. using Python, Faker libraries, or custom generators) Strong understanding of test data management concepts, including data setup, teardown, and dependency handling Experience integration automation with CI/CD pipelines Experience working in data-intensive environments such as: Data Warehouses, Data Lakes, ETL / data pipeline systems Strong experience writing complex SQL queries for large-scale data validation and reconciliation Experience with data masking,