Data Engineer (PySpark & Data Modeling)

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 ResponsibilitiesDesign, develop, and maintain scalable data pipelines using PySparkPerform data modeling (conceptual, logical, and physical) for analytics and reportingBuild and optimize ETL/ELT workflows for large-scale datasetsWork with structured and unstructured data across multiple sourcesEnsure data quality, integrity, and governance standardsCollaborate with data analysts, scientists, and business stakeholdersOptimize performance of Spark jobs and data processing systemsSupport deployment and monitoring of data solutions in productionRequired Skills & QualificationsStrong experience in PySpark and Apache Spark ecosystemHands-on experience in data modeling (Star Schema, Snowflake, etc.)Proficiency in SQL and database technologiesExperience with data warehousing conceptsKnowledge of ETL/ELT tools and frameworksFamiliarity with cloud platforms (AWS / Azure / GCP) is a plusUnderstanding of big data technologies (Hadoop, Hive, Kafka, etc.)Strong problem-solving and analytical skillsPreferred QualificationsExperience in banking/financial services domainExposure to data governance and data quality frameworksKnowledge of CI/CD pipelines and DevOps practices#J-18808-Ljbffr