Lead Data Engineer
Role details
Job location
Tech stack
Job description
The Lead Data Engineer is responsible for building, maintaining, and continuously improving the central HR data lake that aggregates data from all systems. In this role, you will ensure the availability of reliable, analytics-ready datasets for internal tools, AI-driven applications, and cross-functional teams. You will act as a key partner to analysts, IT, and business stakeholders, enabling trusted insights, data-driven decisions, and smooth operation of the enterprise HR data ecosystem. More about the role
- 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
Do you have experience in ServiceNow?, * 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