Custom Software Engineer

Project Role : Custom Software Engineer Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs. Must have skills : Microsoft Azure Databricks Good to have skills : NA Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education

Job Summary We are seeking an experienced Data Engineering Lead with deep expertise in Azure Data Services, Azure Synapse Analytics, and Azure Databricks to design, build, and lead the development of scalable, end-to-end data pipelines. The role involves owning the data architecture from source ingestion to consumption layers, ensuring high performance, reliability, and data quality while mentoring a team of data engineers.

Key Responsibilities : 1. Lead the design, development, and optimization of end-to-end data pipelines from multiple source systems to analytics and reporting layers 2. Architect and implement modern data platforms on Azure using: Azure Data Factory / Synapse Pipelines Azure Synapse Analytics (Dedicated & Serverless SQL pools) Azure Databricks (Delta Lake, Spark) Azure Data Lake Storage (ADLS Gen2) 3. Define and enforce data modeling standards (bronze/silver/gold layers, star/snowflake schemas) 4. Ensure efficient data ingestion, transformation, and orchestration for batch and near-real-time workloads 5. Optimize data pipelines for performance, scalability, cost, and reliability 6. Collaborate with business stakeholders, architects, analysts, and data scientists to align data solutions with business needs 7. Lead and mentor a team of data engineers, conducting code reviews and enforcing best practices 8. Implement data governance, security, and compliance (RBAC, data masking, encryption) 9. Drive CI/CD automation for data pipelines using Azure DevOps or GitHub Actions 10. Monitor, troubleshoot, and resolve pipeline failures and performance issues 11. Participate in architecture reviews and contribute to long-term data strategy