Job description
We are looking for a skilled Data Engineer with strong expertise in PySpark and Data Modeling to join our Data & Analytics team.
The ideal candidate will be responsible for building scalable data pipelines, optimizing data workflows, and supporting advanced analytics initiatives.
Key Responsibilities Design, develop, and maintain scalable data pipelines using PySpark Perform data modeling (conceptual, logical, and physical) for analytics and reporting Build and optimize ETL/ELT workflows for large-scale datasets Work with structured and unstructured data across multiple sources Ensure data quality, integrity, and governance standards Collaborate with data analysts, scientists, and business stakeholders Optimize performance of Spark jobs and data processing systems Support deployment and monitoring of data solutions in production Required Skills & Qualifications Strong experience in PySpark and Apache Spark ecosystem Hands-on experience in data modeling (Star Schema, Snowflake, etc.
) Proficiency in SQL and database technologies Experience with data warehousing concepts Knowledge of ETL/ELT tools and frameworks Familiarity with cloud platforms (AWS / Azure / GCP) is a plus Understanding of big data technologies (Hadoop, Hive, Kafka, etc.
) Strong problem-solving and analytical skills Preferred Qualifications Experience in banking/financial services domain Exposure to data governance and data quality frameworks Knowledge of CI/CD pipelines and DevOps practices
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