USC/GC ONLY Must be local
We are seeking a Data Quality Analyst / Databricks/informatica Implementation LEAD to support enterprise-wide data governance and Lakehouse initiatives. This role will be instrumental in ensuring high-quality well-governed data across domains by partnering with business stakeholders data stewards and technical teams.
You will play a key role in translating business data requirements into trusted datasets within Databricks Unity Catalog while helping establish scalable standards for data quality metadata and lineage.
Key Responsibilities
Data Quality & Profiling
- Develop and maintain data quality rules for critical data elements (CDEs)
- Perform data profiling anomaly detection and root cause analysis
- Collaborate with data stewards to validate business definitions and thresholds
- Monitor and report on data quality metrics and remediation efforts
Databricks Unity Catalog Implementation
- Support rollout of Unity Catalog across business domains
- Assist with onboarding datasets into Bronze Silver Gold (Medallion Architecture)
- Ensure lineage ownership and quality rules are embedded in pipelines
- Implement access controls and sensitivity tagging
Collaboration & Stakeholder Engagement
- Partner with data stewards data owners and business teams
- Translate business needs into standardized data definitions and metadata
- Facilitate working sessions to align on data semantics and domain ownership
- Promote consistent data governance practices across domains
Metadata Lineage & Catalog Management
- Maintain accurate and complete enterprise data catalog metadata
- Document CDEs KPIs and domain-specific terminology
- Validate data lineage from raw ingestion through refined layers
Data Analysis & Issue Resolution
- Investigate and resolve data quality issues raised by stakeholders
- Perform impact analysis for schema or rule changes
- Partner with engineering and business teams on data remediation efforts
Required Qualifications
- 3 5 years of experience in data quality data governance or data analysis
- Hands-on experience with Databricks Delta Lake or similar cloud platforms
- Strong understanding of data quality frameworks and best practices
- Experience working with data catalogs or governance tools
- Proficiency in SQL and data analysis
- Strong communication and stakeholder collaboration skills
Preferred Qualifications
- Experience with Databricks Unity Catalog
- Familiarity with Medallion Architecture (Bronze/Silver/Gold)
- Exposure to data governance frameworks (e.g. DAMA DCAM)
- Experience working with data stewards or data owners
- Knowledge of data modeling or semantic layer design
What Success Looks Like
- You are detail-oriented analytical and collaborative
- You thrive in cross-functional environments
- You are passionate about building scalable data governance and quality programs
You bring a proactive mindset to improving
data trust and usability across the enterprise
USC/GC ONLY Must be local We are seeking a Data Quality Analyst / Databricks/informatica Implementation LEAD to support enterprise-wide data governance and Lakehouse initiatives. This role will be instrumental in ensuring high-quality well-governed data across domains by partnering with business st...
USC/GC ONLY Must be local
We are seeking a Data Quality Analyst / Databricks/informatica Implementation LEAD to support enterprise-wide data governance and Lakehouse initiatives. This role will be instrumental in ensuring high-quality well-governed data across domains by partnering with business stakeholders data stewards and technical teams.
You will play a key role in translating business data requirements into trusted datasets within Databricks Unity Catalog while helping establish scalable standards for data quality metadata and lineage.
Key Responsibilities
Data Quality & Profiling
- Develop and maintain data quality rules for critical data elements (CDEs)
- Perform data profiling anomaly detection and root cause analysis
- Collaborate with data stewards to validate business definitions and thresholds
- Monitor and report on data quality metrics and remediation efforts
Databricks Unity Catalog Implementation
- Support rollout of Unity Catalog across business domains
- Assist with onboarding datasets into Bronze Silver Gold (Medallion Architecture)
- Ensure lineage ownership and quality rules are embedded in pipelines
- Implement access controls and sensitivity tagging
Collaboration & Stakeholder Engagement
- Partner with data stewards data owners and business teams
- Translate business needs into standardized data definitions and metadata
- Facilitate working sessions to align on data semantics and domain ownership
- Promote consistent data governance practices across domains
Metadata Lineage & Catalog Management
- Maintain accurate and complete enterprise data catalog metadata
- Document CDEs KPIs and domain-specific terminology
- Validate data lineage from raw ingestion through refined layers
Data Analysis & Issue Resolution
- Investigate and resolve data quality issues raised by stakeholders
- Perform impact analysis for schema or rule changes
- Partner with engineering and business teams on data remediation efforts
Required Qualifications
- 3 5 years of experience in data quality data governance or data analysis
- Hands-on experience with Databricks Delta Lake or similar cloud platforms
- Strong understanding of data quality frameworks and best practices
- Experience working with data catalogs or governance tools
- Proficiency in SQL and data analysis
- Strong communication and stakeholder collaboration skills
Preferred Qualifications
- Experience with Databricks Unity Catalog
- Familiarity with Medallion Architecture (Bronze/Silver/Gold)
- Exposure to data governance frameworks (e.g. DAMA DCAM)
- Experience working with data stewards or data owners
- Knowledge of data modeling or semantic layer design
What Success Looks Like
- You are detail-oriented analytical and collaborative
- You thrive in cross-functional environments
- You are passionate about building scalable data governance and quality programs
You bring a proactive mindset to improving
data trust and usability across the enterprise
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