Live opening · Posted 11 days ago

Senior Data Engineer (Databricks on Azure)

Luxoft Poland · Poland (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 11 days ago
CompanyLuxoft Poland
LocationPoland (Remote)
Work modeNo
SourceLinkedin
Listed11 days ago

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About the role

Description supplied by the original job listing.

📍work from Poland📍
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).
Mandatory Skills Description:
• 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 Skills Description:
• 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).
Languages:
English: C1 Advanced

Work arrangement
No

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