Senior Data Quality & Governance Engineer

LAM RESEARCH Corporation; Fremont (CA); Hybrid; USD 92,000 - 211,000; Full time

Job summary

Lam Research is seeking a data governance-focused professional to translate governance standards into scalable data quality implementations. You will work across SAP, data engineers, and application teams to implement validation, profiling, and MDM survivorship rules, ensuring trusted data for analytics and AI initiatives.

The role involves building data quality scorecards and lineage, embedding checks in ETL and IDMC pipelines, and collaborating with stakeholders to remediate issues.

Qualifications

• Minimum 8 years of related experience with a relevant degree or equivalent combination.
• 5-7 years of hands-on experience in data quality, metadata management, or governance-focused roles.
• Strong hands-on experience with Informatica Cloud Data Governance & Catalog (CDGC).
• Experience with Informatica IDQ/IDMC or similar data quality solutions.

Responsibilities

• Translate data quality rules into technical implementations using IDQ/IDMC, SQL validations, profiling, scorecards, and pipeline controls.
• Implement data validation, cleansing, standardization, and MDM survivorship rules across enterprise data domains.
• Collaborate with SAP teams to monitor data quality across core data domains.
• Execute enterprise data quality frameworks including rule standardization and threshold management.
• Perform data profiling and validation activities including completeness checks and anomaly detection.

Skills

Data governance

SQL

Data profiling

Data quality

Stakeholder collaboration

Education

Bachelor's degree in Computer Science, Information Systems, Data Engineering

Tools

Informatica IDQ/IDMC

Power BI

SAP

CDGC

Job description

Lam Research is seeking a data governance-focused professional to translate governance standards into scalable data quality implementations. You will work across SAP, data engineers, and application teams to implement validation, profiling, and MDM survivorship rules, ensuring trusted data for analytics and AI initiatives.

The role involves building data quality scorecards and lineage, embedding checks in ETL and IDMC pipelines, and collaborating with stakeholders to remediate issues.