Python with Data Engineer

Job Summary We are looking for a skilled Data Engineer with experience in Python, PySpark, SQL, and Cloud Data Platforms to build and support scalable data pipelines, data transformation processes, and data engineering solutions. Key Responsibilities Design, develop, and maintain ETL/ELT data pipelines. Process and transform large volumes of structured and semi-structured data. Develop scalable solutions using Python, PySpark, and SQL. Optimize data workflows, queries, and data processing performance. Collaborate with business and technical teams to deliver data solutions. Ensure data quality, reliability, and governance standards. Must-Have Skills 5+ years of experience in Data Engineering. Strong hands-on experience with Python for data processing and transformation. Experience with PySpark and distributed data processing frameworks. Strong proficiency in SQL , including complex joins, aggregations, and query optimization. Experience building ETL/ELT pipelines and data ingestion frameworks. Hands-on experience with Azure, AWS, or GCP cloud platforms. Good understanding of Data Warehousing and Dimensional Modeling concepts. Experience working with structured and semi-structured datasets. Good-to-Have Skills Experience with Azure Databricks, Azure Data Factory, or Azure Synapse . Exposure to Kafka, Event Hubs , or other streaming technologies. Experience with CI/CD pipelines and DevOps practices. Working knowledge of Agile/Scrum methodologies and JIRA. BFSI/Investment domain experience or relevant certifications (e.g., LOMA) is an advantage. Skill Python, PySpark, SQL, Data Engineer, ETL, ELT, Azure, AWS, GCP, Databricks, Azure Data Factory, Synapse, Data Warehousing, Dimensional Modeling, Kafka, Big Data, Cloud Data Engineering, Data Pipeline, Spark.