Data Warehouse SME

Project description

We are seeking a highly experienced Data Warehouse Subject Matter Expert (SME) to lead the design, implementation, and governance of enterprise data warehousing solutions. The ideal candidate will bring deep expertise in ETL processes, data architecture, and regulatory data controls, ensuring scalable, high-quality, and compliant data solutions.x`

Responsibilities

• Data Warehouse Architecture & Design - Lead the design and evolution of enterprise data warehouse architecture - Provide expertise on Db2 environments and ensure optimal database performance, scalability, and reliability - Define and implement data modelling standards (conceptual, logical, and physical models) ETL Development & Optimization - Oversee design and development of ETL processes using Informatica, Talend, or similar tools - Ensure efficient data integration, transformation, and loading across multiple systems - Optimize SQL queries and ETL workflows for performance and scalability Batch Processing & Data Flow Management - Govern and monitor batch data flows and scheduling processes - Perform and guide data lineage analysis, ensuring full traceability of data across systems - Conduct impact analysis for system or data changes, identifying downstream dependencies Data Governance & Regulatory Compliance - Define and implement regulatory data controls aligned with compliance requirements - Ensure data quality, consistency, integrity, and auditability across the data landscape - Support enterprise data governance frameworks, policies, and controls Leadership & Stakeholder Engagement - Act as a Subject Matter Expert (SME) for data warehouse and data engineering initiatives - Provide technical leadership and mentoring to data engineers and ETL developers - Collaborate with business, IT, and regulatory stakeholders to align data solutions with organizational needs

SKILLS

Must have

• - Extensive experience with ETL tools such as Informatica, Talend, or equivalent - Strong proficiency in SQL and advanced data transformation techniques - Deep expertise in data modelling and data warehouse design principles - Hands-on experience with Db2 databases and enterprise data warehouse architecture - Strong understanding of batch processing, job scheduling, and data pipelines - Proven experience in data lineage, impact analysis, and metadata management - In-depth knowledge of regulatory requirements and data controls in enterprise environments

Nice to have

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