Job Title: Lead Azure Data Engineer Location: Pleasanton, CA (Hybrid) Job Type: Contracting About the Role: We are looking for a highly skilled Senior Azure Data bricks (ADB) Lead Developer to join our Data Engineering team. This role involves developing large-scale batch and streaming data pipelines on Azure Cloud. Key Responsibilities: • Design and Develop: Create real-time and batch data pipelines using Azure Databricks, Apache Spark, and Structured Streaming. • Data Processing: Write efficient ETL scripts and automate workflows using Python. • Data Integration: Integrate with various data sources and destinations, including DB2, MongoDB, and other enterprise-grade data systems. • Performance Optimization: Tune Spark jobs for optimal performance and cost-effective compute usage on Azure. • Collaboration: Work with platform and architecture teams to ensure secure, scalable, and maintainable cloud data infrastructure. • CI/CD Support: Implement CI/CD for Databricks pipelines and notebooks using tools like GitHub and Azure DevOps. • Stakeholder Communication: Interface with product owners, data scientists, and business analysts to translate data requirements into production-ready pipelines. Required Skills: • experience in data engineering • Python Proficiency: • Data Manipulation: Using libraries like Pandas and NumPy for data manipulation and analysis. • Data Processing: Writing efficient ETL scripts. • Automation: Automating repetitive tasks and workflows. • Debugging: Strong debugging skills to troubleshoot and optimize code. • Database Management: • SQL: Advanced SQL skills for querying and managing relational databases. • NoSQL: Experience with NoSQL databases like MongoDB or Cassandra. • Data Warehousing: Knowledge of data warehousing solutions like Google BigQuery or Snowflake. • Big Data Technologies: • Kafka: Knowledge of data streaming platforms like Apache Kafka. • Version Control: • Git: Using version control systems for collaborative development. • Data Modeling: • Schema Design: Designing efficient and scalable database schemas. • Data Governance: Ensuring data quality, security, and compliance. • Database Management: • DB2: Understanding of DB2 architecture, SQL queries, and database management. • MongoDB: Knowledge of MongoDB schema design, indexing, and query optimization. • Programming Skills: • Proficiency in languages such as Java, Python, or JavaScript to write scripts for data extraction and transformation. • Experience with BSON (Binary JSON) for data conversion. • Cloud Services: • Experience with cloud platforms like AWS or Azure for deploying and managing databases. Preferred Skills: • Experience with Java or Scala in Spark streaming. • Familiarity with Azure services like Data Lake, Data Factory, Synapse, and Event Hubs. • Background in building data platforms in regulated or large-scale enterprise environments.