Key Responsibilities
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Participate in the modernization and migration of current Azure data and analytics systems to the Databricks Lakehouse Platform.
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Support Databricks platform enablement, configuration, and deployment activities.
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Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, Azure Functions, and Databricks.
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Build scalable data integration solutions across Azure Data Lake, Azure SQL Database, Azure Storage (Blob/File), and Databricks.
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Assist in optimizing ingestion and transformation processes for performance, reliability, and cost efficiency.
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Migrate legacy data pipelines, workflows, and processing logic into Databricks notebooks or Delta pipelines.
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Work with cross-functional teams to understand business requirements and translate them into technical solutions.
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Ensure all solutions comply with Marsh MMA standards for security, governance, and data quality.
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Perform data validation, unit testing, troubleshooting, and system performance tuning.
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Document architecture, workflows, design decisions, and operational procedures.
Required Technical Skills
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Strong hands-on experience with:
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Azure Data Factory (ADF)
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SQL / T-SQL
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Azure Functions
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Azure SQL Database
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Azure Data Lake (ADLS Gen2)
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Azure Storage (Blob / File)
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Databricks (Notebooks, Delta Lake, Spark)
Qualifications
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Bachelors degree in Computer Science, Data Engineering, Information Technology, or related field.
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Proven experience working with cloud-based data engineering solutions, preferably in Azure ecosystems.
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Experience supporting cloud migration or modernization initiatives is a plus.
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Strong understanding of ETL/ELT concepts, data modeling, and distributed data processing.
Soft Skills
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Strong analytical and problem-solving mindset.
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Excellent communication and documentation abilities.
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Ability to collaborate with cross-functional teams across technical and business domains.
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Detail-oriented with a focus on quality and compliance.
Originally posted on Himalayas
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