Senior Data Engineer at Capgemini designing and optimizing scalable data architectures on Databricks and GCP. Collaborating across teams to transform business needs into reliable technical solutions.
About the role
- Data Engineer focusing on Azure/Databricks for Atos, building scalable data pipelines and optimizing workloads. Collaborating on complex data systems and ensuring performance tuning for high availability.
Responsibilities
- Build scalable ETL/ELT pipelines and transform large datasets
- Ensure high availability and scalability of data workflows
- Conduct performance tuning while collaborating with the Informatica team
- Manage and optimize batch processes with job schedulers
- Collaborate to deliver optimized solutions for complex data systems
Requirements
- 5-8 years of experience in data engineering
- Strong expertise in Azure Data Factory, Azure Databricks, and Spark SQL
- Hands-on experience in building scalable ETL/ELT pipelines
- Expertise in SQL, PL/SQL, and performance tuning for large-scale data workloads
- Familiarity with job schedulers such as Workload Automation (WLA), Control-M, or Azure Automation
- Collaboration with engineering and product teams to understand complex data systems
Benefits
- Health insurance
- 401(k) retirement plans
- Paid time off
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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