Lead Data Engineer

• Role: Lead Data Engineer
• Location: Bellevue, WA 98006 (2 days a week in Office)
• Type: Contract

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

Detailed Job Description

• 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