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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Data Factory, Databricks, and Azure storage services.
Implement and optimize data transformations with ECL on HPCC and SparkSQL/PySpark on Azure Databricks for large-scale structured and semi-structured data.
Collaborate with business analysts, data scientists, and application teams to deliver reliable data solutions supporting analytics, reporting, and operational needs.
Minimum Requirements
Proficient in SQL, data transformation logic, and data warehousing concepts.
Hands-on experience with Azure Databricks, Spark SQL, PySpark, Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), and Azure SQL / Synapse.
Experience with large-scale data processing and Agile development methodologies.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in building enterprise-grade data pipelines and optimizing performance on Azure and HPCC platforms.
Skilled at working cross-functionally with various teams to translate business requirements into technical solutions.
Strong understanding of SDLC, software development principles, and good knowledge of insurance domain terminology.