Data Engineer Lead​/Architect Azure Databricks and Unity Catalog - Charlottee NC-office

Title: Sr Data Engineer Lead/ Architect with Azure Databricks and Unity Catalog (candidate should be hands on)

Location: Charlottee NC-3 days office

Duration: 10 months

We are looking for an experienced Azure Databricks Engineer with strong expertise in cloud-based data engineering, ETL development, and distributed data processing. The ideal candidate should have solid hands-on experience with PySpark, Delta Lake, Azure Data Factory, and building scalable data pipelines on Azure.

The engineer will work closely with business, Data Architects, and cross-functional teams to design, develop, and optimize data pipelines for enterprise grade analytics and reporting.

• Data Engineering & Pipeline Development
• Design, develop, and optimize ETL/ELT pipelines using Azure Databricks (PySpark).
  Build scalable data ingestion workflows from various structured and unstructured sources.
  Implement transformation logic, data cleansing, enrichment, and validation frameworks.
  Work with Delta Lake to build medallion architecture (Bronze/Silver/Gold layers).
  Develop reusable Databricks notebooks and jobs for production data workflows.
  Azure Cloud & Integration
• Build and orchestrate pipelines using Azure Data Factory (ADF).
  Integrate Databricks with other Azure services-ADLS, Azure SQL, Event Hub, Key Vault, Synapse.
  Optimize compute environments (clusters, pools, autoscaling).
  Implement Dev Ops processes using Git, CICD, Azure Dev Ops.
  Performance, Quality & Governance
• Optimize PySpark jobs for performance and cost efficiency.
  Implement best practices for data governance, security, and access control.
  Troubleshoot production issues and perform root-cause analysis.
  Conduct code reviews ensuring coding standards and data quality.
  Collaboration & Documentation
• Work with Data Architects to define architecture and design patterns.
  Prepare technical documents, solution diagrams, and runbooks.
  Collaborate with business stakeholders to understand requirements and translate them into technical solutions.

• Azure Databricks notebooks, jobs, workflows, Delta Lake.
• PySpark data frames, Spark SQL, optimization & debugging.
• Azure Data Factory (ADF) triggers, pipelines, integration runtime.
• Data Lake Storage (ADLS Gen2) folder structures, partitioning, security.
• CI/CD Git (branching strategies), Azure Dev Ops pipelines.
• SQL strong proficiency in writing optimized queries.

• Azure Synapse Analytics
• Azure Event Hub / Kafka
• Azure Functions
• Data Bricks REST APIs
• Streaming pipelines (Structured Streaming)
• Experience with data modelling
• Knowledge of Lakehouse architecture

• Strong analytical and problem-solving skills.
• Ability to work independently and in cross-functional teams.
• Good communication skills for stakeholder interaction.
• Comfortable working in Agile/Scrum models.