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Manager, Data Quality
Job in
Clifton, Passaic County, New Jersey, 07015, USA
Listed on 2026-09-14
Listing for:
Jobtailor
Full Time
position Listed on 2026-09-14
Job specializations:
-
IT/Tech
Data Analyst, Data Engineering
Job Description & How to Apply Below
- Lead execution and continuous improvement of the data quality strategy across datasets
- Prioritize critical commercial and enterprise data domains based on business impact and risk
- Define and maintain data quality standards, controls, acceptance criteria, and monitoring practices
- Establish quality requirements and readiness checks for onboarding new data sources and products
- Develop and track data quality metrics, scorecards, service expectations, and improvement plans
- Improve data readiness for business, AI, and analytics use cases
- Explore responsible AI-enabled methods for identifying, explaining, prioritizing, and preventing data quality issues
- Lead day-to-day data profiling, validation, reconciliation, exception management, and issue triage across the One Data Platform
- Monitor dashboards and identify trends, recurring defects, and operational risks
- Coordinate root-cause analysis with data engineering, source-system teams, data providers, and business owners
- Drive corrective and preventive actions, track issue ownership, and ensure timely remediation
- Validate that fixes address root causes without downstream business impact
- Partner with commercial business teams, data product owners, master data management, data governance, analytics teams, and external data providers
- Improve the quality, consistency, and timeliness of inbound commercial data
- Provide functional leadership for delivery partners, establish priorities, develop team capabilities, and ensure quality and timely data-quality services
- Bachelor's degree in information systems, data analytics, computer science, engineering, business, life sciences, or related field
- 5+ years of progressive experience in data quality or data management
- Strong knowledge of the pharmaceutical industry and commercial pharma business processes
- Practical knowledge of commercial pharmaceutical data, including several of: professional and account master data, affiliations, sales, claims, market access, payer, field activity, targeting, alignment, and incentive compensation
- Experience defining data quality rules and applying accuracy, completeness, consistency, timeliness, validity, and uniqueness dimensions
- Experience supporting enterprise data platforms, cloud data environments, analytics platforms, or governed data products
- Strong analytical, problem-solving, communication, facilitation, and stakeholder-management skills
- Experience leading cross-functional initiatives, setting priorities, influencing senior stakeholders, and coaching team members or delivery partners
- Experience supporting data used for AI, machine learning, advanced analytics, or semantic data products
- Experience applying AI-assisted techniques for data profiling, anomaly detection, rule generation, matching, classification, root-cause analysis, and issue prioritization
- Proficiency using approved AI assistants for analysis, SQL creation, documentation, and issue investigation while protecting confidential pharmaceutical data
- Strong hands‑on ability with SQL or a scripting language
- Experience designing and implementing automated data‑quality checks
- Working knowledge of ETL/ELT, source-to-target mappings, data lineage, APIs, file-based ingestion, and pipeline monitoring
- Hands‑on experience with Snowflake, AWS, or a comparable modern data platform
- Experience using data quality, metadata, catalog, lineage, governance, master data management, or observability tools
- Experience reviewing logs, tracing data across pipelines, assessing downstream impact, coordinating technical remediation, and working with Git, testing, release management, and controlled deployment
- Preferred: experience in J&J Innovative Medicine or a comparable global pharmaceutical organization
- Preferred: experience with Snowflake,…
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