Senior GCP 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. Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets. The involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.
Requirements
- Proficiency in SQL, Python, Java/Scala, and distributed systems (Spark, Beam).
- Hands-on with BigQuery, Dataflow, Dataproc, Pub/Sub, Composer (Airflow), and Terraform.
- Familiarity with CI/CD, Git, and infrastructure-as-code.
Nice To Haves
- GCP Certifications (e.g., Professional Data Engineer).
- Experience with real-time processing, Vertex AI, or multi-cloud environments.
Responsibilities
- Build and optimize ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Functions.
- Architect and manage BigQuery, Cloud Storage, and Data Fusion for efficient data ingestion, transformation, and storage.
- Mentor junior engineers, review code, and establish data engineering standards, CI/CD, and monitoring (e.g., Cloud Monitoring, Logging).
- Optimize pipeline performance, query efficiency, and GCP cost management (e.g., slot reservations, partitioning).
- Work with data architects, scientists, and analysts to deliver self-service data platforms and support advanced analytics/ML use cases.
- Implement data validation, lineage, and metadata management (e.g., Data Catalog, dbt).
Benefits
- Vacation: 12-25 days, depending on grade
- Company paid holidays
- Personal Days
- Sick Leave
- Medical, dental, and vision coverage
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
