IT - Technology Lead | Cloud Integration | Azure Data Factory (ADF)

Job Title: Lead Data Engineer
Work Location & Reporting Address: Bellevue, WA 98006 (2 days a week in Office)
Vendor Rate: 74.50
Contract duration: 12 months
Target Start Date: 25 Sep 2026
Does this position require Visa independent candidates only? Yes

Interview Process (Is face to face required?): F2F or Team Video Call

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

Project Code: Allocation child code for DM AD Products