Sachin Shetty

Implemented an Enterprise Information Management (EIM) system to centralize data management,
improve data quality, and enhance decision-making capabilities across the organization

• Built and maintained the enterprise metadata hub (DataHub) to improve data discovery, lineage tracking, and governance across critical data assets.
• Designed and implemented complex ETL transformations (Ab Initio, SQL) ensuring high data quality and integrity across systems.
• Performed data profiling and analysis to establish baseline metrics, enabling data-driven quality improvement initiatives.
• Defined and enforced data governance policies, quality metrics, and validation rules, reducing data errors by 30%.
• Partnered with business users and data stewards to translate business requirements into governance and quality solutions.
• Led the migration of the data governance framework to open-source platforms, lowering costs and increasing flexibility.
• Delivered GDPR compliance implementation, aligning governance processes with regulatory requirements.
• Strengthened governance adoption by centralizing metadata and stewardship workflows, promoting collaboration across teams.
• Led design and development of scalable data models for efficient data lakes and datamarts. Optimized end-to-end data pipelines, guaranteeing structured and timely data for analysis. Utilized dbt to transform raw data into valuable business insights. Streamlined data access, enhancing overall analytical capabilities across the organization.

• Developed and maintained the Data Governance Hub , centralizing metadata for improved lineage, traceability, and stewardship .
• Established lineage across Business, Logical, and Physical elements , mapping ETL transformations to ensure complete data transparency.
• Conducted data profiling on critical enterprise datasets (tables/flat files) to identify anomalies and establish baseline quality metrics.
• Designed and executed data quality checks by translating business rules into technical validations using Express>IT , improving accuracy and consistency.
• Automated metadata management processes by developing UNIX scripts and ETL graphs, reducing manual effort and increasing efficiency.
• Performed end-to-end validation of ETL hops in Data Lake systems , ensuring lineage accuracy and compliance with governance standards.
• Supported the upgrade of Ab Initio tools , analyzing impacts on governance workflows and ensuring smooth adoption.

• Supported the setup and maintenance of the Enterprise Analytical Platform (EAP) , a self-service Data Lake integrating ERP data for enterprise-wide reporting and analytics.
• Automated ingestion and processing of ERP data via Kafka → Talend → Hadoop pipelines , enabling scalable and real-time data availability.
• Implemented and maintained the Waterline Data Catalogue , enhancing metadata management, data discovery, and governance across business units.
• Conducted data reconciliation and validation to ensure accuracy, completeness, and trustworthiness of critical datasets.
• Monitored and troubleshot production jobs through TAC , proactively resolving issues to maintain high data availability and integrity.
• Streamlined operational processes by executing and validating configuration object files , supporting governance and quality initiatives.

• Led a team to build and maintain metadata repositories for PWM, Enterprise, Mortgage, Risk & Finance domains, ensuring consistency and governance across business-critical data.
• Established data lineage between Business, Logical, and Physical elements using MHUB , mapping ETL transformations to ensure transparency and traceability.
• Conducted data profiling of large-scale tables, flat files, and HDFS datasets to identify quality gaps and improve reliability.
• Implemented data quality checks by converting business rules into technical rules (Express>IT), improving compliance with regulatory standards (e.g., BCBS 239).
• Validated end-to-end ETL lineage in Data Lake migrations , ensuring accuracy and integrity of critical datasets.
• Collaborated with Data Architects, Stewards, and Analysts to define Critical Data Elements (CDEs) and implement stewardship workflows.
• Designed and developed Ab Initio load graphs and automation scripts, optimizing ETL processes and improving performance.
• Troubleshot and resolved complex data quality and ETL issues within SLA, ensuring uninterrupted business reporting.
• Mentored and guided junior colleagues; recognized for knowledge sharing, leadership, and process improvements .

Key Highlights

• Hands-on with data cleansing, de-duplication, and reconciliation in large-scale banking environments.
• Contributed to metadata-driven governance frameworks for regulatory reporting and compliance.
• Received multiple awards for innovation, automation, and governance delivery excellence .