Python with Data Engineer

Job description

**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.