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Lead Azure Data Engineer

eTeam Inc

Job Title: Lead Data Engineer Work Location & Reporting Address: Bellevue, WA 98006 (2 days a week in Office) Job Details: Minimum years of experience required: 8 Certification needed: NA Must Have Skills: Azure Data factory, Azure Databricks Nice to Have Skills: Scala, Python (PySpark), SQL Key Responsibilities

  • Design, build, and maintain PySpark/SQL pipelines in Azure Databricks for batch and streaming data.
  • Develop robust ingestion from Azure Data Lake Storage (ADLS Gen2), Azure Synapse/SQL, Event Hub, Kafka, and REST/JSON sources.
  • Optimize Spark jobs (partitioning, caching, broadcast joins, AQE) for performance and cost.
  • Implement monitoring and alerting (cluster/job metrics, driver/executor logs).
  • Use Databricks Repos, notebooks, and modular PySpark projects with unit tests (pytest).
  • Build CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for jobs, notebooks, and infrastructure-as-code (Terraform/ARM/Bicep).
  • Manage environments (dev/test/prod), secrets/Key Vault, and configuration promotion.
Required Qualifications (Intermediate Level)
  • 6 years in data engineering; 4 years hands-on with Azure Databricks and Spark.
  • Strong PySpark and SQL skills: DataFrames, joins, window functions, UDFs, incremental loads.
  • Practical experience with Delta Lake, Unity Catalog, and Databricks Jobs/Workflows.
  • Familiarity with Azure services: ADLS Gen2, Azure Key Vault, Event Hub, Azure SQL/Synapse.
  • Version control (Git) and CI/CD experience; basic testing practices (pytest).
  • Ability to optimize Spark jobs and troubleshoot: skew, shuffle, OOM, driver/executor tuning.
  • Solid understanding of data modeling (star schema, medallion/lakehouse), partitioning, and file formats (Parquet/JSON).
  • Airflow, Azure Data Factory orchestration.
  • Terraform for Databricks & Azure resources.
  • Basic Scala and/or SQL Warehouses (Databricks SQL) for BI.
Education • Bachelor's/Master's in Computer Science, Engineering, or related field (or equivalent experience). Certifications (Optional but Valued)
  • Databricks: Data Engineer Associate/Professional
  • Microsoft Azure: DP-203 (Data Engineering on Microsoft Azure), AZ-900 (Fundamentals)
Tools & Tech Stack (Typical)
  • Languages: Python (PySpark), SQL
  • Databricks: Notebooks, Jobs/Workflows, Repos, Unity Catalog, Delta Lake, MLflow
  • Azure: ADLS Gen2, Key Vault, Event Hub, Synapse/SQL, Monitor/Log Analytics
  • DevOps: Git, Azure DevOps/GitHub Actions, Terraform/Bicep eTeam

Vacancy posted 2 days ago
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