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
- Lead Data Engineer responsible for building and maintaining the central HR data lake. Collaborating with analysts and business stakeholders for data-driven decision making.
Responsibilities
- Build and operate a Databricks Lakehouse / Data Lake for enterprise HR data
- Integrate multiple data sources (e.g., SAP SuccessFactors, ServiceNow) to ensure seamless and accurate data flow
- Implement and maintain analytics-ready data models in dbt and convert exploratory datasets into reusable, trusted derived datasets
- Develop, refactor, and optimize data pipelines using AI-assisted coding tools (CLI-first) in Databricks for speed, quality, and maintainability
- Provide curated datasets for internal tools, AI-driven applications, and reporting purposes
- Partner with analysts and business stakeholders to understand data requirements and translate them into robust technical solutions
- Monitor and improve data quality, governance, and performance across all pipelines and datasets
Requirements
- Minimum 5 years of experience in data engineering
- Strong hands-on experience with Databricks, SQL, and Python
- Extensive experience with analytics engineering tools such as dbt
- Skilled in designing modular data systems (Design Thinking approach)
- Experience enforcing data governance and access management practices
- Curious, pragmatic, and solution-oriented mindset
- Careful and disciplined in handling sensitive data
- Strong awareness of privacy, security, and compliance requirements
- Fluent in English
Benefits
- Flexible hybrid working model
- Wide range of training opportunities for professional and personal development
- Exceptional growth opportunities supported by individual development plans
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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