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$160,400–$211,525.
Based on 240 similar postings.
Employer
About Johnson & Johnson
Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices
Johnson & Johnson currently has
63 open roles
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Listed pay typically runs
$117,000–$201,250
across 54 roles with salary data.
Manager, Data Quality leads data quality operations, business-rule validation, profiling, monitoring, and issue remediation to ensure enterprise data products are accurate, consistent, and fit for use in reporting, analytics, and artificial intelligence. This role provides functional leadership for delivery partners while collaborating with commercial teams and data owners to establish ownership and embed preventive controls across the One Data Platform. The successful candidate will manage day-to-day triage, root-cause analysis, and remediation of defects involving pharmaceutical data such as sales, claims, and market access. Required technical skills include SQL or scripting for large dataset profiling, experience with Snowflake or AWS cloud platforms, and proficiency in ETL/ELT processes. The role also requires expertise in data quality dimensions like completeness and timeliness to ensure high-quality data supports critical commercial business decisions within the pharmaceutical industry.
Lead the execution and continuous improvement of data quality strategies across critical commercial and enterprise data domains.
Define and maintain data quality standards, control measures, acceptance criteria, and monitoring practices for the One Data Platform.
Manage day-to-day data profiling, validation, reconciliation, exception management, and issue triage to ensure data is fit for use.
Conduct root-cause analysis with engineering teams and external providers to resolve recurring data defects and operational risks.
Partner with business teams and data owners to establish ownership, embed preventive controls, and improve platform trust.
Develop and track data quality metrics, scorecards, and improvement plans to make data ready for AI and analytics.
Provide functional leadership to delivery partners while developing team capabilities and managing service providers.
What we're looking for
Bachelor's degree in information systems, data analytics, computer science, engineering, business, life sciences, or a related field.
5+ years of progressive experience in data quality or management, including defining controls and leading issue remediation in an enterprise environment.
Strong knowledge of the pharmaceutical industry and commercial pharma business processes.
Hands-on knowledge of commercial pharmaceutical data such as master data, sales, claims, market access, and incentive compensation.
Experience defining data quality rules for accuracy, completeness, consistency, timeliness, validity, and uniqueness.
Experience supporting enterprise data platforms, cloud environments, analytics platforms, or governed data products.
Proficiency in SQL or a scripting language to profile datasets, validate business rules, and investigate anomalies.
Experience with Snowflake, AWS, or comparable modern data platforms (preferred); experience managing service partners or distributed teams (preferred).
Snowflake
SQL
Python
Power BI
Informatica
Collibra
Alation
Power Platform
APIs
Azure DevOps
GitHub
Master Data Management
Data Governance
Data Quality
Metadata Management
Data Lineage
GDPR
CCPA
GLBA
Informatica IDQ
SAP
SQL
Power BI
Python
Spark
Snowflake
Databricks
ETL
Master Data Management
Data Governance
Data Lineage
Metadata Management
Root Cause Analysis
Regression Testing