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Tier-1 brand, metro location, common mid-level data engineer title, and broad skillset increase candidate competition.
Core data engineering skills transfer across industries, but financial services data governance increases domain specificity.
Explicit 3+ years requirement, mandatory data engineering skills, and regulatory data controls increase screening rigor.
Build and maintain scalable data pipelines and feature stores for AI/ML products supporting international markets.
Implement data quality, validation, and monitoring to ensure reliable inputs for AI models and applications.
Collaborate with AI engineers to productionise data flows applying data access, privacy, and regulatory controls across borders.
3+ years applied experience with formal training or certification in software or data engineering concepts.
Proficiency in Python and SQL, with hands-on experience building and maintaining ETL/ELT data pipelines.
Familiarity with distributed data processing platforms such as Spark/Databricks and cloud-native data services.
Bachelor's degree in Computer Science, Data Engineering, or a related quantitative field.
Experienced data engineer at Senior Associate level comfortable in regulated financial services environments (wealth, private banking, asset management).
Technical expertise in modern software engineering practices, data modelling, governance, and compliance for cross-border AI/ML data platforms.
Collaborative operator who participates in design and code reviews and works closely with AI engineers and stakeholders.