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Tier-1 brand, generalist Data Engineer title, and metro location increase applicant density.
Role requires deep data engineering and markets domain expertise, limiting cross-industry transferability.
Many mandatory technical and domain-specific skills for a senior VP role yield high shortlisting strictness.
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Design and build scalable data architecture and production-grade Python pipelines to support Generative AI products across Markets, handling billions of records.
Develop and optimise curated, high-performance data-serving layers enabling low-latency retrieval for AI applications, focusing on PostgreSQL and Parquet storage.
Lead architectural decisions, engineering standards, data quality controls, and operational practices while contributing directly to codebase and CI/CD pipelines.
Extensive hands-on experience in data engineering or software engineering with deep Python expertise.
Strong skills in SQL and relational databases, especially PostgreSQL, with experience in data modelling and performance tuning.
Practical experience processing large-scale datasets using frameworks like Apache Spark, Dask, or equivalent.
Bachelor's or master's degree in Computer Science, Engineering, or relevant quantitative discipline, or equivalent professional experience.
Senior-level engineer with experience building large-scale, high-performance data platforms for AI or data-intensive applications.
Practitioner of pragmatic technology choices and ownership, capable of influencing product and platform architecture in ambiguous environments.
Experience working in finance or capital markets domain with knowledge of data governance, security, and production reliability standards.