Data Warehouse Lead/developer
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Role details
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Job description
Lead the design, development, and implementation of enterprise data warehouse solutions supporting analytics and reporting initiatives Architect and manage ETL/ELT pipelines using Informatica PowerCenter and IDMC to integrate data from multiple source systems Define and enforce data architecture standards, data models, and best practices for scalability and performance Oversee development of data marts, dimensional models (star/snowflake schemas), and optimized warehouse structures Collaborate with business stakeholders to translate requirements into data solutions, dashboards, and reporting frameworks Drive development of BI dashboards and reporting solutions using Tableau, Power BI, and MicroStrategy Ensure data quality, governance, and security compliance, including data validation, lineage, and audit processes Lead and mentor a team of data engineers, ETL developers, and analysts; provide technical guidance and code reviews Optimize query performance, ETL workflows, and database tuning for large-scale datasets Implement automation and data processing solutions using Python to improve efficiency and reduce manual effort Manage data migration, integration, and modernization initiatives, including cloud-based data platforms Coordinate with DevOps and infrastructure teams for deployment, CI/CD, and environment management Establish and monitor KPIs, SLAs, and data pipeline health metrics Provide leadership in data strategy, governance, and roadmap planning aligned with organizational goals Communicate technical solutions and insights effectively to both technical and non-technical stakeholders Nice Add-ons (if needed for JD completeness)
Requirements
Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field 8+ years of experience in data warehousing, ETL, and BI solutions Strong expertise in Informatica (PowerCenter, IDMC), SQL, and data modeling Hands-on experience with Tableau, Power BI, or MicroStrategy Proficiency in Python for data engineering and automation
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