Senior Engineer, VP
Deutsche Bank · Pune · onsite · Posted 1d ago
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About this role
The Senior Engineer will provide technical leadership for the modernisation of legacy SAS-based data solutions into scalable, maintainable Python platforms. The role combines hands-on engineering with architectural ownership, establishing reusable frameworks and robust delivery standards across enterprise data workloads.
Core capabilities:
- Python engineering: Advanced Python development, object-oriented design and clean-code practices, with experience creating modular, reusable libraries and frameworks.
- Workflow orchestration: Deep expertise designing, deploying and maintaining scalable Apache Airflow DAGs, custom operators and scheduling patterns.
- Cloud-native platforms: Strong experience deploying and scaling containerised applications on Google Kubernetes Engine, including Kubernetes configuration and resource management.
- Framework architecture: Proven ability to design, version and maintain shared engineering frameworks, data pipelines and integration components.
- Operational excellence: Experience with observability, profiling, performance tuning, automated testing, CI/CD, GitOps and Docker.
Desirable expertise:
- Hands-on experience with Python Polars for high-performance, memory-efficient data processing.
- Knowledge of Apache Iceberg, including transaction management, schema evolution and file-layout optimisation.
- Experience troubleshooting complex orchestration failures and supporting high-throughput, highly available integrations across shared platforms such as GPFS.
Your key responsibilities:
- Lead the design, development and maintenance of enterprise-grade Python frameworks, reusable libraries and data pipelines that support the migration from SAS to modern Python-based solutions.
- Define engineering standards and provide technical leadership for clean code, object-oriented design, automated testing, versioning and documentation.
- Design, deploy and operate scalable Apache Airflow workflows, including DAGs, custom operators, scheduling patterns, dependency management and failure recovery.
- Deploy and scale containerised workloads on Google Kubernetes Engine, maintaining Kubernetes configurations, resource controls and high-availability services.
- Drive adoption of high-performance data processing and lakehouse technologies, including Python Polars and Apache Iceberg, with effective schema evolution and file-layout optimisation.
Your skills and experience:
- Extensive technology-engineering experience, ideally gained within complex, highly regulated enterprise environments.
- Expert-level Python development skills, including object-oriented design, reusable frameworks, automated testing and clean-code practices.
- Strong hands-on experience with Apache Airflow, Google Kubernetes Engine, relational and distributed databases, GitHub, CI/CD, GitOps and Docker.
- Experience modernising legacy SAS workloads and designing scalable data-processing solutions; knowledge of Python Polars and Apache Iceberg is advantageous.
- Proven people-leadership experience, including managing, coaching and developing a sizeable engineering team and building an inclusive, high-performing culture.
- Demonstrated ability to set technical direction, make sound architectural decisions and balance strategic objectives with hands-on delivery.
- Strong stakeholder-management and communication skills, with the ability to influence senior partners and collaborate across engineering, data, infrastructure, risk and control functions.
- Strong analytical and problem-solving skills, with experience improving reliability, security, performance, observability and operational resilience.
- Proven ability to use AI tools to enhance productivity, optimise workflows and solve business problems, while applying critical judgement to ensure responsible and ethical use of data and AI outputs.
- 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.
How we'll support you:
- Training and development to help you excel in your career.
- Coaching and support from experts in your team.
- A culture of continuous learning to aid progression.
- A range of flexible benefits that you can tailor to suit your needs.
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About Deutsche Bank

Deutsche Bank
Banking
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Frankfurt
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