Lead Engineer, Data Ingestion, VP

Overview

Hands-on Lead Engineer (VP) providing technical leadership for scalable data-ingestion products and services within Risk & Finance Technology at Deutsche Bank.

What you'll do

• Provide hands-on technical leadership for the architecture, design, development and evolution of secure, scalable and resilient data-ingestion platforms.
• Define and communicate technical direction aligned with business priorities, target architecture and divisional engineering standards.
• Lead delivery using Java, Spring Boot, Apache Spark, PySpark, Kubernetes, OpenShift and Google Cloud Platform services such as Cloud Run, Dataproc, GKE and BigQuery.
• Develop reusable frameworks, common components and engineering patterns for batch, API-based, event-driven and distributed data processing.
• Remain actively involved in coding, prototyping, code reviews, troubleshooting and critical technical changes.
• Drive clean-code practices, automated testing, CI/CD, secure deployment, performance engineering and continuous improvement.
• Own production readiness, observability, service-level objectives, capacity, resilience, incident resolution and sustainable remediation.
• Embed information security, data management, risk, audit and regulatory controls throughout the engineering lifecycle.
• Influence architecture and engineering decisions across teams, simplifying the technology estate and reducing duplication, technical debt and operational risk.
• Mentor and coach engineers, resolve technical disagreements and foster an inclusive culture of accountability, collaboration and continuous learning.

What you'll need

• Significant experience in software or data engineering, including technical leadership of complex platforms or products in a large organisation.
• Strong hands-on development experience in Java, Spring Boot and Apache Spark using Java and/or PySpark.
• Strong understanding of distributed processing, SQL, data modelling, APIs, microservices and event-driven integration patterns.
• Practical experience with Kubernetes, OpenShift and Google Cloud Platform, preferably Cloud Run, Dataproc, GKE and BigQuery.
• Experience with CI/CD, automated testing, Git-based workflows, secure engineering and production support for business-critical services.
• Demonstrated ability to define technical direction, develop reusable standards and influence decisions across organisational boundaries.
• Strong analytical, communication and stakeholder-management skills, with the ability to connect engineering decisions to business value, risk and total cost of ownership.
• Experience mentoring engineers and improving the technical capability, delivery discipline and production ownership of wider teams.
• Experience in a regulated environment, preferably banking, financial services, Risk, Finance, Treasury or regulatory reporting.

Nice to have

• Hands-on experience with GitHub Copilot and/or Gemini Code Assist or CLI; Agentic AI applications; specification-driven development; Model Context Protocol; LangChain/LangGraph; Retrieval-Augmented Generation; Polars; Trino; Kafka; data lineage, metadata and data-quality frameworks; Site Reliability Engineering and FinOps.
• Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.

Details

• Location: Pune, India.
• Corporate title: VP.