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Tier-1 brand, metro location, generalist Data Engineer title and broad skill set drive high competition.
Strong financial markets and governance context favors candidates with capital-markets experience, but core data skills remain transferable.
Senior banking role with extensive mandatory data engineering, Python, database, and operational skills enforces high shortlisting strictness.
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Design and build the data foundation for generative AI products across multiple Markets asset classes with a focus on scalable, production-grade Python data pipelines.
Develop and optimise data ingestion, validation, transformation, and serving layers handling billions of records to enable low-latency retrieval for AI applications.
Take long-term ownership of platform architecture, engineering standards, data quality controls, and operational practices while contributing hands-on code.
Extensive hands-on experience in data engineering or software engineering disciplines with strong Python skills.
Proven track record building and operating large-scale data platforms or data-intensive applications.
Strong SQL expertise with experience in PostgreSQL and data modelling, indexing, query optimisation techniques.
Work Experience Required: Not explicitly mentioned in the JD; Educational qualification: bachelor’s/master’s degree in Computer Science, Engineering or equivalent professional experience.
Experienced senior engineer comfortable with ambiguity and driving technical direction for complex data platforms supporting AI use cases in financial markets.
Demonstrated ability to design end-to-end data pipelines with focus on reliability, scalability, operational observability, and security within regulated environments.
Familiarity with distributed data processing (e.g., Spark, Dask), columnar data formats (Parquet), workflow orchestration (e.g., Airflow), and modern software engineering practices including CI/CD and containerized deployments.