Senior Data Engineer

Role Overview EY is seeking an experienced Senior Data Engineer to lead the design and deployment of enterprise-scale data solutions for a leading insurance client. This position offers the opportunity to architect modern data ecosystems using Azure and Databricks, while driving digital transformation initiatives and mentoring technical teams through complex data modernization projects. Key Responsibilities - Design and implement scalable high-performance data pipelines using Azure services including ADF, ADLS, and Synapse - Lead comprehensive data engineering initiatives spanning data ingestion, transformation, and data serving across the enterprise - Collaborate with architects, business stakeholders, and cross-functional teams to define and execute data strategies - Ensure data quality, governance, security compliance, and adherence to insurance industry regulations - Drive modernization efforts of legacy platforms such as DB2 and Datastage to cloud-based architectures - Optimize ETL and ELT processes for improved performance, scalability, and cost efficiency Required Qualifications - 5 to 10 years of hands-on experience in data engineering or related technical roles - Advanced proficiency with Azure services including ADF, ADLS, and Synapse - Strong expertise in Python, SQL, and Apache Spark for large-scale data processing - Deep knowledge of data architecture, data warehousing, and lakehouse concepts - Demonstrated experience in insurance or BFSI domain with enterprise data environments - Knowledge of CI/CD pipelines, DevOps practices, and version control systems - Bachelor's or Master's degree in Computer Science, Information Technology, or related field Why Join Us Join EY and work on transformative data engineering projects for leading global organizations. You will have the opportunity to mentor junior engineers, work with cutting-edge technologies, and make a significant impact on enterprise data transformation initiatives.

- 5-10 years data engineering experience - Azure services expertise including ADF, ADLS, Synapse - Databricks platform proficiency - Advanced Python and SQL skills - Apache Spark knowledge - Insurance or BFSI domain experience - Data warehousing and lakehouse architecture understanding - ETL/ELT process optimization skills - CI/CD and DevOps knowledge - Version control systems experience - API integration capabilities - Mulesoft experience preferred - DB2 and Datastage knowledge preferred - Microsoft Azure Data Engineer certification preferred - Databricks Data Engineer certification preferred - Data governance framework experience preferred - Strong analytical and problem-solving abilities - Technical leadership and mentoring capabilities - Excellent communication skills