Senior Python Engineer for AI-Ready Data & Governance

Intellias; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Intellias is seeking a hands-on senior Python engineer with strong data engineering experience to advance AI agent capabilities and secure, scalable data foundations in an investment management context.

You will build catalogue, semantic, entitlement, and analytical layers enabling agents to access enterprise data safely and effectively. Expect collaboration with data governance and security disciplines to ensure data quality and trust.

Qualifications

• 6+ years building production Python software.
• Strong data engineering fundamentals and scalable pipelines.
• Experience with analytical/query engines (DuckDB/Trino/Spark/ClickHouse).
• Hands-on with LLM/agent applications: retrieval, vector stores, tooling.
• Knowledge of data governance: catalog, metadata, lineage, access control.
• Focus on data quality and trustworthy golden sources.

Responsibilities

• Build production-grade Python services and data pipelines over large data stores.
• Choose and implement appropriate query/analytical engines per workload.
• Develop catalogue, metadata, lineage and semantic layers for data discovery.
• Implement data access controls at the data source and for AI agents.
• Build agent-facing data access: retrieval, vector search, APIs with permissions.
• Apply LLMs to data work with humans in the loop and quality checks.
• Ensure golden sources, deduplication and data-quality checks at the source.
• Contribute to discovery and pragmatic, costed solution planning.

Skills

Python engineering

Data engineering

SQL

Parquet/columnar data

Data governance

LLM/agent apps

RAG / vector databases

RBAC/ABAC

Data quality

Tools

DuckDB

Trino

Spark

ClickHouse

Job description

Intellias is seeking a hands-on senior Python engineer with strong data engineering experience to advance AI agent capabilities and secure, scalable data foundations in an investment management context.

You will build catalogue, semantic, entitlement, and analytical layers enabling agents to access enterprise data safely and effectively. Expect collaboration with data governance and security disciplines to ensure data quality and trust.