Data Quality & Governance Technical Analyst (Level 4)

The Global Information Systems Group is dedicated to the success of Lam through providingbest-in-class and innovative information system solutions and services. Together, we supportusers globally with data, information, and systems to achieve their business objectives.

• Translate business-defined data quality rules into technical implementations.
• Implement data validation, cleansing, and standardization rules, including MDM survivorship logic.
• Enable the execution of data quality frameworks, including rule standardization, threshold management, and alignment to Critical Data Elements (CDEs).
• Perform data profiling and validation, including null checks, pattern analysis, duplicate detection, and anomaly identification.
• Configure and support CDGC capabilities, including data catalog onboarding and metadata ingestion.
• Enable business glossary mapping, CDE classification, and data product onboarding into the marketplace.
• Support and validate data lineage across systems to ensure traceability and facilitate impact analysis.
• Embed data quality checks and pass/fail gates into data pipelines (IDMC, ETL, and SQL).
• Monitor data quality scorecards, track defects, and collaborate on issue classification and prioritization.
• Perform root cause analysis (RCA), validate fixes through regression testing, and recommend structural improvements.
• Develop and support data quality dashboards.

• A minimum of 8 years of related experience with a Bachelor's degree in Computer Science or a related field; or 6 years of related experience with a Master's degree; or 3 years of related experience with a PhD; or an equivalent combination of education and experience.
• 6-8 years of management experience.
• 6 years of hands-on experience in data quality, data engineering, or governance-focused technical roles.
• Strong hands-on experience with Informatica CDGC and data catalog tools, including metadata curation, dataset onboarding, and data quality visibility.
• Experience with business glossaries, data lineage, and governed metadata management.
• Strong proficiency in SQL and data pipeline development, including ETL, IDMC, and SQL-based workflows.
• Strong analytical skills, with experience in data profiling, data quality validation, and root cause analysis (RCA).

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3 days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.

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