Data Quality Analyst (CDGC / Informatica)

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.

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 implementing data quality controls, enabling CDGC capabilities, and driving visibility through data catalogs, lineage, metadata, and quality scorecards, you will help ensure that downstream business processes, analytics, reporting, and AI initiatives consume trusted and reliable data.This role is highly hands-on and execution-focused, requiring close collaboration with data stewards, governance leads, SAP teams, data engineers, and application teams to proactively identify, resolve, and prevent data quality issues at scale.

• Translate business-defined data quality rules into technical implementations using Informatica IDQ/IDMC, SQL validations, profiling rules, scorecards, and pipeline controls.
• Implement data validation, cleansing, standardization, and MDM survivorship rules across enterprise data domains.
• Partner with SAP functional teams to implement and monitor data quality controls across Customer, Supplier, Material, and Finance master data domains.
• Execute enterprise data quality frameworks, including rule standardization, threshold management, and alignment to Critical Data Elements (CDEs).
• Perform data profiling and validation activities, including completeness checks, duplicate analysis, pattern validation, referential integrity checks, and anomaly detection.
• Configure and support CDGC capabilities, including dataset onboarding, metadata ingestion, catalog enrichment, governed asset management, and business glossary mapping.
• Support CDE classification, governed data asset onboarding, and data product registration within CDGC and Data Marketplace.
• Support and validate technical and business data lineage across SAP, master data, analytics, and downstream platforms for traceability and impact analysis.
• Enable and maintain data quality rule mapping, scorecards, dashboards, and data health visibility within CDGC.
• Embed data quality validation checks and pass/fail control gates within IDMC, ETL, and SQL-based data pipelines to prevent invalid data from propagating downstream.
• Develop, enhance, and maintain data quality scorecards and dashboards using CDGC, Power BI, and related reporting tools.
• Monitor data quality scorecards and dashboards, track defects, support issue classification, and partner with stakeholders on remediation activities.
• Perform root cause analysis (RCA), validate fixes through regression testing, and recommend structural and upstream process improvements to prevent recurring issues.

• A minimum of 8 years of related experience with a Bachelor's degree in Computer Science, Information Systems, Data Engineering 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.
• 5-7 years of hands-on experience in data quality, metadata management, master data management, data engineering, or governance-focused technical roles.
• Strong hands-on experience with Informatica Cloud Data Governance & Catalog (CDGC), including metadata curation, dataset onboarding, catalog management, data quality rule mapping, and data quality visibility.
• Hands-on experience with Informatica IDQ, IDMC, or similar data quality solutions for profiling, validation, rule implementation, scorecards, and monitoring.
• Strong working knowledge of SAP master data domains, including Customer, Supplier, Material, and Finance, with experience supporting data quality, governance, and lifecycle management processes across ERP environments.
• Experience working with business glossaries, Critical Data Elements (CDEs), data lineage, and governed metadata management.
• Strong SQL skills and experience developing or supporting ETL, IDMC, and SQL-based data pipelines.
• Experience performing data profiling, data validation, issue investigation, root cause analysis (RCA), regression testing, and remediation tracking.
• Strong analytical, problem-solving, and stakeholder collaboration skills.

• Experience with SAP S/4HANA, SAP MDG, or enterprise master data management initiatives.
• Experience building or supporting data quality scorecards and dashboards using Power BI or similar visualization platforms.
• Experience with cloud data platforms such as SILK, Snowflake, Databricks, or equivalent modern data environments.
• Familiarity with MDM concepts including match/merge, survivorship, validation rules, and reference data management.
• Experience supporting data product enablement, self-service analytics, or data marketplace initiatives.
• Basic scripting experience using Python, Spark, or related technologies.

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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