Senior Data Platform Engineer

Overview

Senior hands-on engineering role within Deutsche Bank's eDiscovery and Archiving Technology group, leading the modernization of an enterprise data platform that supports defensible eDiscovery decisions, and leading technical design and development of a new GCP-based data platform.

What you'll do

• Personally design, code, unit test, review, profile, debug, deploy, and support production-grade Oracle PL/SQL packages, Java services, APIs, batch components, data-processing modules, and integration frameworks.
• Produce reference implementations for complex or high-risk capabilities.
• Own key design decisions for modular decomposition of legacy data-platform capabilities, including custodian identity, employment history and aliases, application and data-source coverage, archive configurations, retention context, refinement rules, and identification outputs.
• Extract and rationalize business logic embedded in legacy code, database routines, manual backend processes, and operational knowledge, separating essential control logic from accidental complexity.
• Design, develop and maintain the on-premise data platform through substantial hands-on Java coding, relational data models, advanced SQL and PL/SQL, controlled interfaces, automated ingestion, reconciliation, and operational tooling.
• Design for coexistence and transition between on-premise and GCP components, including secure connectivity, data synchronization, reconciliation, dual-run controls, cutover, rollback, and progressive retirement of legacy components.
• Develop scalable ingestion and onboarding patterns for HR, application, archive, account, migration, retention and other source data, including bulk loads, schema validation, data-quality controls, source traceability, and controlled schema evolution.
• Establish a trusted data model and source-of-truth hierarchy for custodian identity and source coverage, with provenance, effective dating, confidence, exception handling, and full traceability.
• Design services and configuration capabilities that reduce hard-coded change and expose reusable capabilities to EDI and other approved consumers through secure APIs and events.
• Build end-to-end auditability into the platform, capturing data lineage, rule versions, decision context, user and system actions, overrides, approvals, and evidence.
• Define engineering standards for Java, Python, SQL, APIs, data modeling, testing, observability, resilience, security, CI/CD, and Infrastructure as Code, driving adoption through code reviews and design reviews.
• Lead technical design forums and influence engineers, architects, product partners, and control stakeholders toward robust, simple, and supportable solutions.
• Coach technical team members through pair programming, design walkthroughs, reference implementations, and detailed code reviews.
• Implement comprehensive observability across services and pipelines, including data-quality metrics, health monitoring, structured logging, tracing, alerting, reconciliation, failure recovery, and operational dashboards.
• Lead performance engineering and root-cause analysis across Java services, databases, data pipelines, and integrations, including JVM behavior, concurrency, memory, SQL execution plans, indexing, and batch-window optimization.
• Partner with Architecture, Information Security, Data Governance, Compliance, and operations teams on access control, encryption, retention, residency, resilience, disaster recovery, change governance, and production evidence.
• Drive incremental delivery through proofs of concept, walking skeletons, reusable platform components, automated tests, and measurable migration outcomes.

What you'll need

• Strong relational database engineering and advanced SQL skills, including complex queries, analytical functions, execution plan analysis, indexing, data modeling, stored procedures, and performance tuning.
• Hands-on Java expertise, including modern Java, object-oriented and functional design, collections, concurrency, JVM internals, memory and performance tuning, exception handling, dependency management, and production debugging.
• Good practical Python coding knowledge for data processing, automation, validation, orchestration, utilities, and integration, with the ability to review Python design and code quality.
• Strong experience building enterprise platforms, REST APIs, microservices, batch processing, event-driven integration, persistence frameworks, security controls, and automated testing.
• Proven ability to lead complex technical designs and influence experienced engineers through architecture reasoning, code-level credibility, constructive challenge, and practical implementation guidance.
• Strong data-platform engineering experience across on-premise and cloud environments, including ingestion, transformation, data quality, reconciliation, metadata, lineage, effective-dated data, and governed publication of trusted datasets.
• Experience re-architecting or modernizing a legacy, business-critical application through phased decomposition, coexistence, migration, dual run, reconciliation, and controlled cutover.
• Strong API-first and metadata-driven design capability, including service contracts, versioning, idempotency, schema evolution, backward compatibility, error models, and secure system integration.
• Strong knowledge of data modeling for identity, configuration, historical and relationship data, including normalization, provenance, effective dating, and source-of-truth rules.
• Experience designing automated tests, including unit, component, integration, contract, data reconciliation, regression, performance, and failure-recovery testing.
• Strong DevSecOps experience using Git, CI/CD, code-quality and security scanning, artifact management, containerization, Terraform, configuration management, secrets management, and repeatable environment promotion.
• Experience designing observable and resilient services with structured logging, metrics, traces, health checks, retries, deadletter handling, restartability, high availability, and disaster recovery.
• Ability to translate security, privacy, data residency, retention, audit, and change-control requirements into enforceable technical designs and code in a regulated enterprise.
• Excellent written and verbal communication, with the ability to present design options and trade-offs, build technical consensus, and document decisions.
• Proven ability to leverage AI tools to enhance productivity and optimise workflows, applying critical judgment to ensure responsible and ethical use of data and AI outputs.

Nice to have

• Strong PL/SQL knowledge.
• Hands-on GCP data-platform experience with BigQuery, Cloud Storage, Cloud Composer/Airflow, Dataflow, Pub/Sub, Cloud Run and/or GKE, with sound judgment on when each service is appropriate.

Details

• Location: Pune, India.
• Corporate Title: Assistant Vice President.