Applied AI ML Associate Senior-Data Engineer
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What you'll do
- Builds and maintains scalable data pipelines and feature stores supporting the team's AI/ML products, from source systems through to production
- Implements data quality, validation, and monitoring so downstream models and applications can trust their inputs
- Structures and models data for retrieval-augmented generation, feature engineering, and analytics workloads
- Partners with AI engineers to productionise data flows for agentic AI and ML use cases
- Applies data access, privacy, and residency controls to firm-wide and cross-border regulatory standards
- Contributes to design discussions and code reviews, growing towards greater technical ownership
- Uses AI coding tools (e.g., Claude Code, GitHub Copilot) as part of day-to-day development
What they're looking for
- Formal training or certification on software or data engineering concepts and 3+ years applied experience
- Proficiency in Python and SQL, and familiarity with modern software engineering practices (testing, code review, version control)
- Hands-on experience building and maintaining data pipelines and ETL/ELT workflows
- Exposure to distributed data processing and platforms such as Spark / Databricks
- Working knowledge of cloud-native data services, containerisation, and CI/CD
- Understanding of data modelling and warehousing concepts
- Ability to communicate clearly with engineers, data scientists, and stakeholders
- BSc in Computer Science, Data Engineering, or a related quantitative field
Nice to have
- Industry-recognised data engineering certification (e.g., AWS Certified Data Engineer - Associate (DEA-C01), or similar)
- Exposure to data foundations for ML / LLM workloads (feature stores, vector stores, RAG pipelines)
- Exposure to financial services, particularly wealth, private banking, or asset management
- Familiarity with data governance, lineage, and privacy tooling
- Familiarity with JPM-internal data and AI/ML infrastructure for internal candidates
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
We're looking for a hands-on data engineer ready to grow their career. Join the ranks of top talent at one of the world's most influential companies.
As a Applied AI ML Associate Senior -Data Engineer at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you will build and maintain the data pipelines and platforms that our agentic AI and machine learning products run on. Working alongside senior engineers, you will develop data ingestion, transformation, and quality checks so the team's models and applications are fed timely, well-governed, model-ready data across international markets.
This is a Senior Associate-level role and an integral part of the IPB Tech AIML team, reporting to the AIML Team Lead.
Job Responsibilities
- Builds and maintains scalable data pipelines and feature stores supporting the team's AI/ML products, from source systems through to production
- Implements data quality, validation, and monitoring so downstream models and applications can trust their inputs
- Structures and models data for retrieval-augmented generation, feature engineering, and analytics workloads
- Partners with AI engineers to productionise data flows for agentic AI and ML use cases
- Applies data access, privacy, and residency controls to firm-wide and cross-border regulatory standards
- Contributes to design discussions and code reviews, growing towards greater technical ownership
Uses AI coding tools (e.g., Claude Code, GitHub Copilot) as part of day-to-day development
Required qualifications, capabilities, and skills
- Formal training or certification on software or data engineering concepts and 3+ years applied experience
- Proficiency in Python and SQL, and familiarity with modern software engineering practices (testing, code review, version control)
- Hands-on experience building and maintaining data pipelines and ETL/ELT workflows
- Exposure to distributed data processing and platforms such as Spark / Databricks
- Working knowledge of cloud-native data services, containerisation, and CI/CD
- Understanding of data modelling and warehousing concepts
- Ability to communicate clearly with engineers, data scientists, and stakeholders
- BSc in Computer Science, Data Engineering, or a related quantitative field
Preferred qualifications, capabilities, and skills
- Industry-recognised data engineering certification (e.g., AWS Certified Data Engineer - Associate (DEA-C01), or similar)
- Exposure to data foundations for ML / LLM workloads (feature stores, vector stores, RAG pipelines)
- Exposure to financial services, particularly wealth, private banking, or asset management
- Familiarity with data governance, lineage, and privacy tooling
- Familiarity with JPM-internal data and AI/ML infrastructure for internal candidates
Company
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