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