Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines and data processing workflows on Azure-based data platforms.
Develop high-performance data engineering solutions using Python, PySpark, SQL, PL/SQL, and Azure Databricks while ensuring data quality and reliability.
Collaborate with business stakeholders, solution architects, and data modellers to translate business requirements into scalable technical solutions.
Support data migration, modernization, optimization, and performance tuning initiatives while following engineering best practices.
Skills Required
3+ yrs of Strong hands-on experience in Python, PySpark, SQL, PL/SQL, and Azure Databricks for developing scalable data engineering solutions.
Valuable understanding of ETL/ELT frameworks, distributed data processing, Azure data services, and performance optimization techniques.




Experience building and maintaining enterprise-grade data pipelines, data integration solutions, and cloud-based data platforms.
Ability to troubleshoot complex data engineering issues and write efficient, optimized code for large-scale data processing.
Strong analytical and problem-solving skills with the ability to deliver scalable, high-quality data solutions.
Excellent communication and stakeholder management skills, with experience working collaboratively in Agile cross-functional teams.
Good to Have
Experience working with Microsoft Access (AccessDB) and VBA Macros for legacy application support, automation, or migration projects.

📌 Data Engineer (India)
🏢 EXL
📍 India