Enterprise Data Integration Lead - Informatica, SQL, Cloud Platforms & Data Quality

Requirements

• Bachelor's or Master's degree in Data Engineering, Computer Science, or a related discipline
• 6 to 7 years supporting enterprise-scale data

Additional Information

Job Summary Synechron is seeking an experienced ETL Informatica Developer to design, develop, and optimize scalable data integration solutions supporting data warehousing, business intelligence, and analytics initiatives. This role involves building robust ETL workflows, ensuring high data quality, and supporting enterprise data governance and performance standards. The ideal candidate will leverage extensive experience with Informatica tools and databases to deliver reliable, high-performance data pipelines aligned with organizational objectives and industry best practices. Software Requirements Required Software Proficiency: Informatica PowerCenter / IDQ (latest version support) - extensive experience in developing, configuring, and maintaining ETL workflows in enterprise environments SQL (Oracle, SQL Server, PostgreSQL, or DB2) - strong skills in complex query writing, stored procedures, and performance tuning supporting data validation and transformation Unix/Linux scripting (Bash, Shell) - proficiency supporting automation, job scheduling, and scripting support Data governance platforms supporting metadata management and data quality processes Data warehouse concepts: star schema, snowflake schema, SCDs, fact and dimension tables - supporting data modeling and schema design Preferred Software Skills: Cloud platforms (Azure, AWS, GCP) supporting cloud-based data integration and migration (preferred) Data quality tools and frameworks supporting enterprise data validation and cleansing Automation tools supporting deployment and environment management support Overall Responsibilities Design, develop, and maintain scalable ETL workflows supporting enterprise data warehouses and analytics platforms Optimize data pipelines for performance, scalability, and reliability in alignment with business goals Collaborate with data architects, business analysts, and data scientists to gather requirements and deliver data transformation solutions Support data migration, schema changes, and data refresh processes supporting regulatory and operational standards Conduct data validation, reconciliation, and quality assurance activities supporting compliance and data integrity Automate data load processes, support job scheduling, and manage workflow dependencies Improve existing ETL frameworks and implement best practices for reusable, efficient, and maintainable data pipelines Maintain thorough documentation of ETL processes, data flow diagrams, and operational procedures Technical Skills (By Category) Languages & Data Tools (Essential): SQL (Oracle, SQL Server, PostgreSQL, DB2): supporting complex data transformations and validation Informatica PowerCenter / IDQ: designing, developing, and troubleshooting workflows/supporting data pipelines Unix/Linux scripting (Bash, Shell): automating routine jobs and processes Data & Schema Management: Data modeling, schema design, and data validation supporting enterprise data warehousing Cloud & Infrastructure Support: Support for cloud data platforms (Azure, AWS, GCP) supporting migration, storage, and processing (preferred) Tools & Platforms: Metadata management, data quality, and data governance frameworks supporting compliance and data lineage support Performance & Optimization: Query tuning, workflow scheduling, and performance monitoring tools supporting large data volumes Experience Requirements 6 to 7 years supporting enterprise data warehousing and ETL workflows in large-scale, regulated environments Proven experience developing, testing, and maintaining scalable ETL workflows supporting analytics and migration projects Strong knowledge of data quality, validation, and reconciliation supporting compliance standards Experience with cloud data platforms (preferred), supporting hybrid cloud or cloud-native architecture Demonstrated ability to troubleshoot complex data pipeline issues and optimize performance in enterprise environments Day-to-Day Activities Develop, test, and optimize ETL workflows supporting enterprise data warehousing and analytics Collaborate with data architects, business analysts, and data scientists to gather requirements and refine data pipelines Monitor data load performance, troubleshoot pipeline failures, and address data discrepancies Support data migration activities, schema modifications, and data refreshes supporting compliance and operational excellence Automate data workflows, manage job dependencies, and support environment configurations Ensure data security, quality, and metadata management adhering to industry and regulatory standards Document ETL processes, workflows, and data architecture supporting operational transparency and compliance Participate in code reviews, performance tuning, and process improvement initiatives supported by agile practices

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