Senior Data Platform Engineer

Position Overview
Job Title: Senior Data Platform Engineer
Corporate Title: Assistant Vice President
Location: Pune, India
Role Description
This position sits within Deutsche Bank's eDiscovery and Archiving Technology group and will play a leading engineering role in the modernization of a critical enterprise data platform. The platform provides identification, data-source intelligence, and configuration-control capabilities supporting defensible eDiscovery decisions across Legal, Compliance, HR, Audit, and Investigations. The successful candidate will strengthen and evolve the existing on-premise data platform while leading the technical design and hands-on development of a new generation GCP-based data platform. This is a deeply hands-on engineering role, not a pure architecture, coordination, or people-management position. It requires expert-level Java engineering, strong data-platform design capability, practical Python coding knowledge, and the ability to convert complex legacy business logic into modular, testable, observable, and auditable services and data products. The role will set engineering direction, lead designs, influence technical team members through code-level credibility, and remain directly accountable for coding, code reviews, debugging, troubleshooting, and production delivery.
What We’ll Offer You
As part of our flexible scheme, here are just some of the benefits that you’ll enjoy,
Best in class leave policy.
Gender neutral parental leaves
100% reimbursement under childcare assistance benefit (gender neutral)
Sponsorship for Industry relevant certifications and education
Employee Assistance Program for you and your family members
Comprehensive Hospitalization Insurance for you and your dependents
Accident and Term life Insurance
Complementary Health screening for 35 yrs. and above
Your Key Responsibilities
Operate as a deeply hands-on lead engineer: 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; distinguish essential control logic from accidental complexity and prevent a like-for-like migration of legacy constraints.
Design, develop & maintain the on-premise data platform through substantial hands-on Java coding, supported by relational data models, advanced SQL and PL/SQL, controlled interfaces, automated ingestion, reconciliation, and operational tooling. Improve maintainability, test coverage, documentation, release quality, and production supportability through direct implementation.
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 without disrupting eDiscovery obligations.
Develop scalable ingestion and onboarding patterns for HR, application, archive, account, migration, retention, and other source data; support 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 explicit provenance, effective dating, confidence, exception handling, and full traceability of why an identification or downstream task was produced.
Design services and configuration capabilities that reduce hard-coded change, enable controlled onboarding and offboarding of applications and data sources, 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 needed to explain and defend identification outcomes.
Define engineering standards for Java, Python, SQL, APIs, data modeling, testing, observability, resilience, security, CI/CD, and Infrastructure as Code; use code reviews and design reviews to drive consistent adoption across the team.
Lead technical design forums and influence engineers, architects, product partners, and control stakeholders toward robust, simple, and supportable solutions; challenge weak designs constructively and translate target architecture into implementable increments.
Influence and coach technical team members through pair programming, hands-on design walkthroughs, reference implementations, and detailed code reviews while holding a high bar for correctness, readability, automated testing, performance, resilience, and operational readiness.
Implement comprehensive observability across services and pipelines, including data-quality metrics, usage and health monitoring, structured logging, tracing, alerting, reconciliation, failure recovery, and actionable 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, throughput, latency, and batch-window optimization.
Partner with Architecture, Information Security, Data Governance, Compliance, and operations teams to ensure designs meet requirements for 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 rather than producing architecture artifacts without executable implementation.
Your Skills And Experience
Strong relational database engineering and advanced SQL skills, including complex queries, analytical functions, execution plan analysis, indexing, data modeling, stored procedures, and performance tuning; strong PL/SQL knowledge is highly desirable.
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 even though Java is the primary engineering skill.
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 clear architecture reasoning, code-level credibility, constructive challenge, and practical implementation guidance.
Strong data-platform engineering experience across both on-premise and cloud environments, including ingestion, transformation, data quality, reconciliation, metadata, lineage, effective-dated data, and governed publication of trusted datasets.
Hands-on GCP data-platform experience with BigQuery, Cloud Storage, Cloud Composer/Airflow, Dataflow, Pub/Sub, Cloud Run and/or GKE, together with sound judgment on when each service is appropriate.
Experience re-architecting or modernizing a legacy, business-critical application through phased decomposition, coexistence, migration, dual run, reconciliation, and controlled cutover rather than a single high-risk rewrite.
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, dimensional or analytical models where appropriate, provenance, effective dating, and source-of-truth rules.
Experience designing high-quality automated tests, including unit, component, integration, contract, data reconciliation, regression, performance, and failure-recovery testing, with testability designed into the platform.
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, disaster recovery, and meaningful service-level indicators.
Ability to work in a regulated enterprise and translate security, privacy, data residency, retention, audit, and change-control requirements into enforceable technical designs and code.
Excellent written and verbal communication, with the ability to present design options and trade-offs, build technical consensus, document decisions, and maintain

Work arrangement
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