Lead Azure Data Engineer

Key Responsibilities

• Participate in the modernization and migration of current Azure data and analytics systems to the Databricks Lakehouse Platform
  .

• Support Databricks platform enablement, configuration, and deployment activities.

• Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Azure Functions, and Databricks.

• Build scalable data integration solutions across Azure Data Lake
  , Azure SQL Database
  , Azure Storage (Blob/File), and Databricks.

• Assist in optimizing ingestion and transformation processes for performance, reliability, and cost efficiency.

• Migrate legacy data pipelines, workflows, and processing logic into Databricks notebooks or Delta pipelines.

• Work with cross-functional teams to understand business requirements and translate them into technical solutions.

• Ensure all solutions comply with Marsh MMA standards for security, governance, and data quality
  .

• Perform data validation, unit testing, troubleshooting, and system performance tuning.

• Document architecture, workflows, design decisions, and operational procedures.

• Bachelors degree in Computer Science, Data Engineering, Information Technology, or related field.

• Proven experience working with cloud-based data engineering solutions, preferably in Azure ecosystems.

• Experience supporting cloud migration or modernization initiatives is a plus.

• Strong understanding of ETL/ELT concepts, data modeling, and distributed data processing.

• Strong analytical and problem-solving mindset.

• Excellent communication and documentation abilities.

• Ability to collaborate with cross-functional teams across technical and business domains.

• Detail-oriented with a focus on quality and compliance.