Data Engineering Lead - Cloud Modernization & Reconciliation

Capgemini; New York (NY); On-site; USD 136,000 - 155,000; Full time

Job summary

Capgemini in New York seeks a seasoned leader to drive the Global Reconciliation Platform. You will lead a team of Spark/Scala Data Engineers, delivering BAU operations, platform modernization, and cloud migration to AWS, while ensuring alignment with business objectives and risk controls.

You will partner with Product, Operations, Finance, and Technology to design scalable data processing, reconciliation, and exception-management solutions for high-volume financial data, mentoring engineers

Qualifications

• 10+ years of experience in Technology Delivery, Data Engineering, or Technical Project Management within Banking or Financial Services.
• Proven experience leading teams of Spark, Scala Engineers.
• Strong understanding of reconciliation platforms, financial controls, transaction lifecycles, exception management, and operational risk processes.

Responsibilities

• Lead a team of Spark/Scala Data Engineers for the Global Reconciliation Platform.
• Deliver BAU, platform modernization, regulatory, and cloud-migration initiatives to AWS.
• Shape designs with Solution Architects and align tech with business goals.
• Collaborate with stakeholders to provide reconciliation capabilities for controls and exception management.
• Ensure platform stability and production issue resolution.
• Mentor engineers and promote continuous improvement.

Skills

Leadership

Cloud migration

Agile delivery

Tools

Spark

Scala

AWS

Job description

Capgemini in New York seeks a seasoned leader to drive the Global Reconciliation Platform. You will lead a team of Spark/Scala Data Engineers, delivering BAU operations, platform modernization, and cloud migration to AWS, while ensuring alignment with business objectives and risk controls.

You will partner with Product, Operations, Finance, and Technology to design scalable data processing, reconciliation, and exception-management solutions for high-volume financial data, mentoring engineers