Senior Technical Lead

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 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 rigorous internal governance - from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

Responsibilities

• Target-state architecture design - define and own the target-state AWS architecture across compute, data, and orchestration layers

• HLD/LLD ownership - produce and own High-Level Design and Low-Level Design documentation for migration workloads

• ARB submissions - prepare and present architecture proposals to the Architecture Review Board for approval

• Technical decisions - make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)

Pattern definition - define reusable architecture and migration patterns for use across teams/pods

• Agentic AI framework architecture - design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

Must have

5+ years experience

hands-on experince with AWS Migration

AWS Glue, Step Functions, Lambda, EventBridge - deep hands-on experience designing solutions using these core AWS services

IaC (Terraform) - strong experience defining and managing infrastructure as code with Terraform

Data platform architecture - proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale

PySpark - hands-on experience with PySpark for large-scale data processing

CI/CD - experience designing and implementing CI/CD pipelines for infrastructure and data workflows

AI/ML frameworks - working knowledge of AI/ML frameworks and their application within architecture design

GitHub Copilot - practical experience using GitHub Copilot within development/architecture workflows

Nice to have

AWS certification (Data Analytics Specialty or Solutions Architect)

Experience with BI tools (QuickSight, Tableau, Power BI)

Infrastructure as Code experience (Terraform/CloudFormation)

Industry experience relevant to your business

Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)

experince in financial domain