Senior Data Engineer

Project description

Senior data engineer developing and operating Databricks / Spark pipelines and Delta Lake lakehouse layers on Azure for the Client. Accountable for pipeline reliability, data freshness and dataset quality against agreed SLAs. Key tasks • Develop and operate Databricks / Spark pipelines (PySpark, SQL, Delta Live Tables or Workflows). • Design Delta Lake / lakehouse layers (bronze–silver–gold), partitioning and Unity Catalog governance. • Build ETL/ELT jobs and orchestration with Azure Data Factory and/or Airflow; manage dependencies and retries. • Implement data-quality checks and validation (expectations, reconciliation, anomaly alerts). • Tune Spark job performance and cluster cost (autoscaling, Photon, job clusters, spot). • Manage schema evolution and change control; document lineage and transformations.

Responsibilities

• Pipeline reliability and data freshness against agreed SLAs.
• Accuracy and completeness of curated datasets.
• Schema change management and backward compatibility for downstream consumers.
• Documentation of data lineage and transformations (Unity Catalog, data catalogue).

SKILLS

Must have

• Bachelor's degree in Computer Science, Engineering, Information Systems or a related field, or equivalent practical experience.
• 7+ years in data engineering, of which 3+ on Databricks / Apache Spark and 2+ on Azure data services (ADF, ADLS, Delta Lake).
• Databricks (Workflows, Delta Live Tables, Unity Catalog), Apache Spark (PySpark, Spark SQL), Delta Lake.
• Azure: Data Factory, Data Lake Storage Gen2, Key Vault, Event Hubs, Synapse or SQL DB; Azure DevOps CI/CD for notebooks and jobs.
• Python and SQL at expert level; data modelling (dimensional, data vault) and ELT design.
• Orchestration (ADF, Airflow), data-quality frameworks (Great Expectations, DLT expectations), monitoring and alerting.
• Performance and cost tuning of Spark workloads; Git-based development and testing of pipelines.

Nice to have

• Databricks Certified Data Engineer Professional; Azure DP-203. • Streaming (Structured Streaming, Kafka / Event Hubs). • dbt, Power BI semantic models, MLflow. • Experience in financial services, sovereign wealth / investment holding or other regulated enterprise environments. • Experience working with distributed teams (onsite UAE with nearshore India / offshore Poland squads).