Data Quality & Governance Technical Analyst (Level 4)

Lam Research•Fremont, CA

8d•$92,000 - $211,000•Hybrid

About The Position

The Global Information Systems Group is dedicated to the success of Lam through providing best-in-class and innovative information system solutions and services. Together, we support users globally with data, information, and systems to achieve their business objectives. You will play a critical role in translating data governance standards into scalable technical implementations that improve data trust and usability across the enterprise. By embedding data quality controls, enabling CDGC capabilities, and driving data visibility through cataloging, lineage, and metadata management, you will ensure that downstream analytics, reporting, and operational systems consume high-quality, reliable data. This role focuses on hands-on execution and continuous improvement, ensuring that data issues are proactively identified, resolved, and prevented at scale.

Requirements

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).

Nice To Haves

Experience with Informatica IDQ, IDMC, or similar tools for data quality rule implementation and scorecard development.
Experience with Power BI or similar tools to build, analyze, and maintain data quality dashboards and metrics.
Exposure to SAP master data domains, including Customer, Supplier, Material, and Finance.
Experience with cloud platforms such as SILK, Snowflake, or Databricks.
Familiarity with Master Data Management (MDM) concepts, including survivorship and validation rules.
Basic scripting experience in Python, Spark, or similar technologies.

Responsibilities

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.