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Tier-1 brand plus common Data Engineer title, tempered by senior, niche generative-AI finance specialization.
Core data-engineering skills transfer broadly, but markets and generative-AI finance experience increases domain specificity.
Numerous mandatory technical skills, VP seniority, and financial production requirements imply stringent screening.
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Design and build scalable data architecture and pipelines in Python for greenfield Generative AI products across Markets, handling billions of records with low-latency access.
Develop and maintain production-grade data services and curated datasets supporting conversational AI and other AI applications, ensuring quality, security, and operational reliability.
Shape platform architecture, engineering standards, data models, and operational practices with long-term ownership of the data foundation.
Extensive hands-on experience in data engineering or software engineering with production-grade Python development expertise.
Strong SQL skills and experience with relational databases, specifically PostgreSQL, including performance tuning and data modeling.
Experience processing large-scale datasets using frameworks like Apache Spark, Dask, or equivalent; and knowledge of ETL/ELT architectures including incremental processing, idempotency, and failure recovery.
Work Experience Required: Not explicitly mentioned in the JD.
Senior engineer comfortable with end-to-end data platform design and operation in complex, high-scale AI and financial data environments.
Experienced in integrating diverse, complex market data and collaborating closely with AI and software engineers in a product-driven agile context.
Able to take ownership and influence technical direction in ambiguous situations, balancing pragmatic technology choices with long-term platform reliability and security.