Senior Data Engineer
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Key skills for this role
About the Role
Xebia is seeking a Senior Data Engineer in Abu Dhabi to drive a Databricks-centric Lakehouse. The role involves building and maintaining Delta Lake tables, Lakeflow pipelines, and AI/BI layers.
Key Skills for This Role
Responsibilities
- Design and build robust data ingestion and orchestration pipelines with Databricks (Lakeflow Jobs/Workflows) as the primary platform
- Build and maintain scalable Delta Lake tables under Unity Catalog — schema design, access controls, lineage tracking, and data quality across bronze/silver/gold layers
- Build declarative ETL pipelines using Databricks Lakeflow, incorporating CDC, incremental processing, and data quality validation
- Design and maintain semantic layers, metrics, and certified datasets to support Genie spaces and AI/BI dashboards
- Configure and maintain Lakeflow Connect (or similar) integrations for ingesting SharePoint and other external data sources
- Apply Unity Catalog governance controls — access policies, data masking, audit logging
- Uphold strong engineering practices (CI/CD, version control, testing)
Requirements
- 7 10 years of experience
- Strong hands on Databricks expertise — PySpark/SQL, Workflows/Jobs orchestration, Delta Lake, Unity Catalog
- Working knowledge of Azure Data Factory
- Experience with Lakeflow (Declarative Pipelines/Connect) including CDC and data quality validations
- Exposure to Databricks AI/BI or Genie (semantic layers, certified datasets)
- Familiarity with CI/CD and version control (Git, Databricks Repos/Asset Bundles)
- Demonstrated ability to own deliverables fully and resolve issues independently
- Strong communication skills for working with business/analytics stakeholders
Full Job Posting
About the Role
- We're seeking a proactive, hands on Senior Data Engineer to drive our Databricks centric Lakehouse — Delta tables governed by Unity Catalog, Lakeflow pipelines, and AI/BI layers like Genie and dashboards.
Key Responsibilities
- Pipeline Orchestration: Design and build robust data ingestion and orchestration pipelines, with Databricks (Lakeflow Jobs/Workflows) as the primary platform and Azure Data Factory supporting legacy/external needs — taking full ownership of pipeline reliability and the transition toward Databricks n
- Lakehouse Data Engineering: Build and maintain scalable Delta Lake tables under Unity Catalog — schema design, access controls, lineage tracking, and data quality across bronze/silver/gold layers.
- Lakeflow Pipeline Development: Build declarative ETL pipelines using Databricks Lakeflow, incorporating CDC, incremental processing, and data quality validation.
- AI/BI & Genie Enablement: Design and maintain semantic layers, metrics, and certified datasets to support Genie spaces and AI/BI dashboards, enabling natural language querying and self service analytics.
- SharePoint/External Source Integration: Configure and maintain Lakeflow Connect (or similar) integrations for ingesting SharePoint and other external data sources into the Lakehouse with minimal manual effort.
- Governance & Best Practices: Apply Unity Catalog governance controls — access policies, data masking, audit logging — and uphold strong engineering practices (CI/CD, version control, testing).
Must Have Skills
- Strong hands on Databricks expertise — PySpark/SQL, Workflows/Jobs orchestration, Delta Lake, Unity Catalog.
- Working knowledge of Azure Data Factory.
- Experience with Lakeflow (Declarative Pipelines/Connect) including CDC and data quality validations.
- Exposure to Databricks AI/BI or Genie (semantic layers, certified datasets).
- Familiarity with CI/CD and version control (Git, Databricks Repos/Asset Bundles).
- Demonstrated ability to own deliverables fully and resolve issues independently.
- Strong communication skills for working with business/analytics stakeholders.
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