This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world’s largest financial market infrastructure companies handles its data pipelines. During this Mobilisation Phase, you’ll work jointly with client’s engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration. The work is technically rich and highly collaborative: you’ll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client’s rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision. This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment
Responsibilities:
— Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж — Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios; -Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process; -GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks; -Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale
Mandatory Skills Description:
— Python — strong hands-on Python development experience for building tools and automation — GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling — Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools — AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications — GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows — Automation frameworks — experience designing and building automation frameworks/tooling from scratch — Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy — Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)
