Senior Data Engineer
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Summary
Senior Data Engineer at Luxoft building and operating Databricks/Spark (PySpark, Delta Lake) pipelines and lakehouse layers on Azure for a client, owning ETL/ELT orchestration (Data Factory/Airflow), data-quality checks, and Spark performance/cost tuning against agreed SLAs.
Private Medical & Dental care & Life Insurance
Internal Mobility program - possibility of rotation between projects, locations, accounts
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
What is relevant to 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.
What is nice to have
- 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).