Job Summary
Experienced data professional skilled in building and scaling data quality and governance foundations from scratch in lowstructure environments collaborating across business and IT to deliver AIready data ecosystems.
Establish, advance, and mature data quality and governance capabilities in a greenfield, lowmaturity data environment. Support enterprise analytics, BI, and AI/ML readiness through SQL/ETL engineering, data profiling, validation, stewardship, metadata management, and earlystage data architecture. Drive longterm improvement of data standards, definitions, lineage, and quality processes.
Responsibilities
Data Quality & Engineering
- Perform data audits, profiling, validation, anomaly detection, and quality gap identification.
- Develop automated data quality rules and validation logic using TSQL, SQL Server, stored procedures, and indexing strategies.
- Build and maintain SSIS packages for validation, cleansing, transformation, and errordetection workflows.
- Troubleshoot ETL/ELT pipelines, data migrations, integration failures, and data load issues.
- Conduct rootcause analysis and implement preventive and longterm remediation solutions.
- Optimize SQL queries, tune stored procedures, and improve data processing performance.
- Document audit findings, validation processes, data flows, standards, and quality reports.
- Build dashboards and reports for data quality KPIs using Power BI/Tableau.
Data Stewardship & Governance
- Define, maintain, and enforce data quality standards, business rules, data definitions, and governance policies.
- Monitor datasets for completeness, accuracy, timeliness, consistency, and compliance.
- Ensure proper and consistent data usage across departments and systems.
- Maintain business glossaries, data dictionaries, metadata repositories, and lineage documentation.
- Partner with IT, data engineering, and business teams to support governance initiatives and compliance requirements.
- Provide training on data entry, data handling, stewardship practices, and data literacy.
- Collaborate with crossfunctional teams to identify recurring data issues and recommend preventive solutions.
GreenField / LowMaturity Environment
- Architect initial data quality frameworks, validation layers, governance artifacts, and ingestion patterns.
- Establish scalable data preparation workflows supporting analytics, BI, and AI/ML readiness.
- Mature data quality and governance processes from adhoc to standardized, automated, and measurable.
- Drive adoption of data quality and governance practices across business and technical teams.
- Support longterm evolution of enterprise data strategy and governance maturity.
Qualifications
- Advanced TSQL, SQL Server development, debugging, and performance tuning.
- SSIS development, deployment, and troubleshooting.
- Data profiling, validation rule design, quality scoring, and measurement techniques.
- ETL/ELT pipeline design, debugging, and optimization.
- Data modeling (conceptual, logical, physical).
- Metadata management and lineage documentation.
- Reporting and dashboarding with Power BI, Tableau, or similar tools.
- Strong documentation and communication skills.
Preferred Skills
- Knowledge of DAMADMBoK, DCAM, MDM concepts, and governance frameworks.
- Experience in lowmaturity/greenfield data environments.
- Familiarity with AI/ML data readiness and featurestorealigned data structuring.
- Cloud data engineering exposure (Azure, Databricks, Google Cloud Platform).
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