Description
Establish, advance, and mature data quality and governance capabilities in a green‑field, low‑maturity data environment. Support enterprise analytics, BI, and AI/ML readiness through SQL/ETL engineering, data profiling, validation, stewardship, metadata management, and early‑stage data architecture. Drive long‑term improvement of data standards, definitions, lineage, and quality processes.
MUST HAVE 8-10 years of Data Quality & Engineering
Perform data audits, profiling, validation, anomaly detection, and quality gap identification.
Develop automated data quality rules and validation logic using T‑SQL, SQL Server, stored procedures, and indexing strategies.
Build and maintain SSIS packages for validation, cleansing, transformation, and error‑detection workflows.
Troubleshoot ETL/ELT pipelines, data migrations, integration failures, and data load issues.
Conduct root‑cause analysis and implement preventive and long‑term remediation solutions.
Optimize...