Lead Data Engineer
About The Position
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
Requirements
- Azure, AWS, or Google Cloud experience
- Infrastructure as Code (IaC) experience
- CI/CD pipelines experience
Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT frameworks.
- Architect and implement modern data platforms, data lakes, and cloud-based data warehouses.
- Build robust batch and real-time data processing solutions.
- Define and implement data modeling standards, including dimensional and semantic models.
- Ensure high availability, performance, scalability, and security of data infrastructure.
- Lead a team of data engineers by providing technical guidance, code reviews, and mentoring.
- Establish engineering standards, best practices, and development frameworks.
- Drive technical design discussions and architecture reviews.
- Translate business requirements into scalable and maintainable technical solutions.
- Collaborate with enterprise architects and solution teams to align data strategies with organizational goals.
- Implement data quality checks, validation frameworks, and monitoring mechanisms.
- Ensure adherence to data governance, privacy, security, and compliance standards.
- Develop metadata management, lineage, and cataloging solutions.
- Partner with governance and compliance teams to implement data stewardship practices.
- Design and manage cloud-native data solutions using Azure, AWS, or Google Cloud.
- Optimize performance and cost efficiency of data platforms.
- Automate deployment processes using Infrastructure as Code (IaC) and CI/CD pipelines.
- Monitor system health, troubleshoot issues, and improve platform reliability.
- Partner with business leaders, analytics teams, and product owners to prioritize data initiatives.
- Support data scientists and analysts with curated, trusted datasets.
- Present architecture recommendations and project updates to senior leadership.
- Drive cross-functional alignment on enterprise data strategy
Benefits
- Flexible work
- Healthcare including dental, vision, mental health, and well-being programs
- Financial well-being programs such as 401(k) and Employee Share Ownership Plan
- Paid time off and paid holidays
- Paid parental leave
- Family building benefits like adoption assistance, surrogacy, and cryopreservation
- Social well-being benefits like subsidized back-up child/elder care and tutoring
- Mentoring, coaching and learning programs
- Employee Resource Groups
- Disaster Relief
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
