Roles and Responsibilities

• As the Azure Databricks Tech Lead, you will play a pivotal role in architecting, implementing, and optimizing Azure Databricks solutions to support our data engineering and analytics initiatives. You will collaborate closely with cross-functional teams to understand business requirements, design scalable data solutions, and lead the execution of projects.
• Technical Leadership: Lead the design, development, and implementation of Azure Databricks solutions, ensuring alignment with business objectives and best practices.
• Architecture and Design: Architect robust and scalable data pipelines and analytics solutions on Azure Databricks, leveraging services such as Apache Spark, Delta Lake, and MLflow.
• Data Engineering: Develop ETL processes, data ingestion pipelines, and data transformations to support data integration and analytics requirements.
• Performance Optimization: Optimize Azure Databricks workloads for performance, reliability, and cost-efficiency, utilizing techniques such as partitioning, caching, and resource management.
• Collaboration: Collaborate with data scientists, analysts, and business stakeholders to understand requirements, translate them into technical solutions, and deliver actionable insights.

Preferred Skills

• Extensive experience with Azure Databricks, Azure Data Lake, and Azure Data Factory.
• Strong proficiency in Python or Scala programming languages for data engineering and data pipeline development.
• Deep understanding of big data technologies and distributed computing frameworks.
• Experience with data modeling, data warehousing, and ETL concepts.
• Experience with SQL and NoSQL databases.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and collaboration skills.

Qualifications

• Bachelor's degree or higher in Computer Science, Data Science, or a related field.
• Azure certifications in data engineering or data analytics are a plus.