Lead Azure Data Engineer

Develop robust ingestion from Azure Data Lake Storage (ADLS Gen2), Azure Synapse/SQL, Event Hub, Kafka, and REST/JSON sources. "Build CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for jobs, notebooks, and infrastructure-as-code (Terraform/ARM/Bicep).

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