Project description
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 workflows - 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
SKILLS
Must have
- - 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)
Nice to have
Experience in financial domain
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Senior Data Engineer (AI/Tooling) employer: Luxoft
As a leading bank, we pride ourselves on fostering a dynamic and inclusive work environment that encourages professional growth and collaboration. Our Training Business Analyst role offers the opportunity to engage in impactful projects while working alongside talented teams dedicated to compliance and innovation. With a strong commitment to employee development and a culture that values diverse perspectives, we provide our staff with the tools and support needed to thrive in their careers.
