Data Engineer - PySpark & Informatica

GSSTech Group

Key Responsibilities

• Design and develop scalable enterprise data engineering solutions using PySpark and Informatica platforms
• Build and model Raw Data Vault structures with strong understanding of:
• Source system data structures
• Data retention policies
• Data partitioning strategies
• Drive data reusability and reduce data duplication while optimizing performance
• Define and implement enterprise data architecture standards and best practices
• Create data exchange standards to support reusable and decoupled architectures
• Define standards for data archival, retention, and purging
• Identify and document critical data elements across enterprise source systems
• Collaborate with data engineers, architects, and source system SMEs to establish data engineering principles and governance standards
• Support large-scale data transformation and analytics initiatives
• Contribute to CI/CD-enabled data engineering and deployment environments
• Ensure compliance with enterprise data quality, governance, and security standards

Required Skills & Experience

• Strong hands-on experience in:
• PySpark
• Informatica Platform Engineering
• Enterprise Data Engineering
• Big Data Ecosystems
• Strong expertise in:
• Data Architecture
• Data Strategy & Roadmaps
• Enterprise Data Management
• Data Warehousing & Analytics Solutions
• Strong understanding of:
• Dimensional Modeling
• Star & Snowflake Schemas
• Slowly Changing Dimensions (SCD)
• Role-playing Dimensions
• Dimensional Hierarchies
• Data Classification
• Experience transforming traditional Data Warehouse environments into Big Data-based architectures
• Expertise in:
• Data Quality
• Data Profiling
• Data Governance
• Data Security
• Metadata Management
• Data Archival
• Experience with cloud-native principles, architectures, and deployments
• Strong exposure to Continuous Integration (CI) and Continuous Deployment (CD) environments
• Strong analytical, troubleshooting, and problem-solving capabilities