Lead Data Engineer

Overview

As Manager, Data Engineering Lead, you will steer the end-to-end data engineering and analytics platform for SwapClear and Listed Rates, aligning with a cloud-native Snowflake architecture. You’ll drive the migration from legacy systems, ensure availability and governance, and partner with architecture and governance groups to deliver measurable reporting capabilities. This role combines hands-on engineering with leadership to scale a systemically important data platform. You’ll shape data-driven outcomes for members, clients, and internal stakeholders.

Pay / Benefits

• healthcare
• retirement planning
• paid volunteering days
• wellbeing initiatives

Responsibilities

• Own the end-to-end data solutions for reporting and analytics across SwapClear and Listed Rates
• Lead safe migration from legacy Oracle/Informatica to cloud architecture
• Oversee multi-year delivery and decommissioning of legacy systems
• Define and evolve the Strategic Cloud data platform for SwapClear and Listed Rates
• Ensure platform availability, performance, resilience, and security
• Support delivery planning with Product Owners and Delivery Leads
• Partner with Group Architecture, Data Governance, and Product/business partners
• Collaborate with Quality engineering to uphold SDLC quality and cloud-native practices
• Build strong relationships with internal/external partners to align on quality goals

Key requirements

• 15+ years in software engineering, with 5+ years in a technical leadership role
• Experience leading enterprise-scale Snowflake data platform implementations
• ELT data architectures using dbt or similar
• Cloud data lake and data warehouse solutions
• SQL, PL/SQL and Python for data-centric solutions
• Data warehouse modelling and immutable/incremental/versioned data architectures
• Data governance, lineage and control frameworks
• Informatica PowerCenter or similar
• Quality-first approach and seniority to influence architecture and governance
• AI experience in data engineering/migrations use cases
• Detail-oriented with strong problem-solving and deep-dive capability

• leadership and credibility to influence governance bodies
• data-driven decision making
• strong collaboration across cross-functional teams
• Snowflake (or similar) data platform
• ELT architectures and dbt
• cloud data lake/warehouse

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