Manager, Data Quality

Jobtailor; New Jersey; On-site; USD 120,000 - 165,000; Full time

Job summary

Jobtailor is seeking an experienced Data Quality Lead to drive the data quality strategy across datasets within the One Data Platform. You will prioritize critical commercial domains, define standards, and monitor quality metrics to ensure timely, accurate data for analytics and AI use cases.

You will lead profiling, validation, and issue triage, coordinating with data engineering, product teams, and external providers to implement corrective actions and prevent recurrence.

Qualifications

• 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.
• 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.

Responsibilities

• 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.

Skills

Data Quality Management

SQL Proficiency

Pharmaceutical Industry Knowledge

AI-Assisted Data Techniques

Cross-Functional Leadership

Education

Bachelor's degree in information systems or related field

Tools

Snowflake

AWS

Databricks

Azure

Data Governance Tools

Job description

• 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

Requirements

• 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, Databricks, AWS, Azure, or similar cloud data platforms
• Preferred: experience managing service partners, data vendors, or distributed delivery teams

Core Competencies

Demonstrates expertise in data quality management, including the establishment of standards, metrics, and monitoring practices. Proficient in leveraging AI techniques for data profiling and ensuring data readiness for analytics and business use cases.

Highest-signal resume keywords

• Data Quality Management
• SQL Proficiency
• Pharmaceutical Industry Knowledge
• AI-Assisted Data Techniques
• Cross-Functional Leadership

Hard Skills

• Data Quality Standards
• Data Profiling
• Data Validation
• Data Reconciliation
• Automated Data Quality Checks
• ETL/ELT Processes
• Data Lineage
• Anomaly Detection
• Root-Cause Analysis
• Data Quality Metrics

Soft Skills

• Analytical Skills
• Problem-Solving
• Communication
• Facilitation
• Stakeholder Management

Industry Keywords

• Pharmaceutical Data
• Commercial Pharma Processes
• Data Quality Dimensions
• Data Management
• Cloud Data Environments

Tools & Technologies

• Snowflake
• AWS
• Databricks
• Azure
• Data Governance Tools
• Master Data Management Tools
• Observability Tools
• AI Assistants
• APIs
• Pipeline Monitoring