About the Role
The position involves designing, developing, and maintaining data warehousing solutions that support enterprise reporting and analytics. The role requires building ETL/ELT pipelines, ensuring data quality, and supporting governance practices.
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Key Responsibilities
Data Warehouse Design & Development
- Design and develop dimensional and/or normalized data models (e.g., star/snowflake) to support enterprise reporting and analytics.
- Implement and maintain DWH layers (staging, integration/core, and presentation/marts).
- Establish and maintain data standards (naming conventions, keys, reference/master data alignment).
ETL/ELT Development (Data Pipelines)
- Build and maintain ETL/ELT pipelines to ingest data from multiple sources (ERP, operational systems, flat files, APIs).
- Develop reusable transformations using SQL and ETL tools to standardize business logic and KPIs.
- Schedule, monitor, and optimize jobs for reliability and performance (incremental loads, CDC where applicable).
Data Quality, Controls, and Governance Support
- Implement automated data quality checks (completeness, validity, duplicates, reconciliations).
- Perform root cause analysis for data issues and work with business/IT stakeholders to resolve upstream causes.
- Document data lineage, mapping specifications, and transformations to support auditability and trust.
- Support data governance practices (certified datasets, definitions, and KPI alignment).
Required Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or equivalent practical experience.
- 3–6 years of hands-on experience in ETL/ELT and data warehousing.
- Strong SQL (advanced queries, performance tuning).
- Proven experience designing and implementing DWH data models.
- Experience integrating ERP/data (e.g., Oracle JDE or similar ERP) is highly desirable.
- Working knowledge of data quality frameworks and reconciliation methods.
- Strong documentation skills.
Technical Skills
- SQL (advanced): performance tuning, indexing concepts, query optimization
- Data warehousing concepts: staging → core → marts, dimensional modeling
- ETL/ELT tooling: SSIS.
- RDBMS experience (any of): SQL Server, DB2, Snowflake, etc.
