Position: Data Engineer

Experience: 3+ Years

Joining Preference: Immediate / Early Joiners only

About the Role

We are looking for a skilled Data Engineer with strong hands-on experience in Python, SQL, PySpark, and cloud data platforms (AWS/Azure). The ideal candidate will have experience designing and developing scalable ETL/ELT pipelines, processing large datasets, and building reliable data solutions for analytics and reporting.

Key Responsibilities

· Design, develop, and maintain scalable ETL/ELT data pipelines.

· Develop data processing solutions using Python and PySpark.

· Write and optimize complex SQL queries, stored procedures, and database objects.

· Build and maintain cloud-based data pipelines using AWS or Azure data services.

· Ingest, transform, and integrate structured and semi-structured data from multiple data sources.

· Perform data transformation, cleansing, validation, and integration.

· Build and maintain effective data models for analytics and reporting.

· Monitor data pipelines and troubleshoot performance, reliability, and data quality issues.





· Optimize data processing jobs for scalability and performance.

· Collaborate with Data Analysts, BI developers, Software Engineers, and other cross-functional teams.

· Ensure data quality, reliability, security, and governance across data platforms.

· Follow best practices for code quality, testing, documentation, version control, and CI/CD.

Required Skills

· Strong programming skills in Python.

· Strong hands-on experience with SQL, including joins, CTEs, window functions, query optimization, and performance tuning.

· Hands-on experience with PySpark / Apache Spark for large-scale data processing.

· Strong understanding of ETL/ELT concepts and data integration.

· Experience working with cloud platforms such as AWS or Azure.

· Experience with cloud-based data engineering, ETL, and big data technologies.

· Good understanding of data warehousing and data modeling concepts.

· Ex

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