Data Engineer – Azure & Databricks

Job Description

Marsh MMA is undertaking a major initiative to modernize and unify its fragmented Azure data and analytics landscape. The organization aims to migrate existing systems to a Databricks-native services platform, enabling reduced operational complexity, minimized data duplication, lower latency, and improved compliance, security, and scalability.

We are seeking a skilled Data Engineer to support Databricks platform enablement and lead the migration of existing Azure-based systems to the new Lakehouse architecture.

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.

Required Technical Skills

• Strong hands-on experience with:
  • Azure Data Factory (ADF)
  • SQL / T-SQL
  • Azure Functions
  • Azure SQL Database
  • Azure Data Lake (ADLS Gen2)
  • Azure Storage (Blob / File)
  • Databricks (Notebooks, Delta Lake, Spark)

Qualifications

• Bachelor’s 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.

Soft Skills

• 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.