Jobs → Data & Analytics → Data Engineer

About the Role We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and enterprise data solutions. The ideal candidate should have strong hands-on experience with Python, SQL, PySpark, cloud platforms, ETL/ELT processes, and modern data warehousing technologies. Key Responsibilities • Design, develop, and maintain scalable data pipelines for large-scale data processing. • Build and optimize ETL/ELT workflows to extract, transform, and load data from multiple sources. • Develop data processing solutions using Python, PySpark, and SQL. • Implement data integration solutions across cloud platforms and enterprise applications. • Design and maintain data lakes, data warehouses, and lakehouse architectures. • Work with structured, semi-structured, and unstructured data. • Develop and optimize complex SQL queries and data transformation logic. • Implement data quality checks, validation, monitoring, and error handling. • Collaborate with data architects, business analysts, and report • Ensure data security, governance, and compliance standards are followed. Requirements • Strong hands-on experience in Data Engineering. • Advanced knowledge of Python, SQL, and PySpark. • Experience with Apache Spark and distributed data processing. • Strong understanding of ETL/ELT development and data pipeline architecture. • Experience with cloud platforms such as AWS, Azure, or GCP. • Hands-on experience with data warehousing technologies such as Snowflake, Databricks, Redshift, or BigQuery. • Experience with data modeling, data integration, and data transformation. • Knowledge of relational and NoSQL databases. • Experience with workflow orchestration tools such as Apache Airflow. • Familiarity with Git, CI/CD, and deployment processes. • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.