Manager/Sr. Manager, Data Foundations & Integration

PharmaEssentia U.S.A.•Burlington, MA

4d•$190,000 - $245,000•Hybrid

About The Position

The Global Data & AI Enablement team is seeking an experienced Manager/Sr. Manager, Data Foundations & Integration to lead data ingestion, integration, governance, and the day-to-day operation of the enterprise data foundation supporting commercial analytics, data products, and AI capabilities. Reporting to the Data Strategy & Operations Lead, this role will oversee the onboarding and reliable delivery of data from internal systems and external data providers into the company’s data warehouse environment. External vendors will perform the hands-on backend engineering required to build, deploy, and operate ETL pipelines. The Manager/Sr. Manager will provide internal oversight of these activities, including defining requirements and priorities, reviewing proposed solutions, setting quality and service expectations, monitoring vendor performance, and approving production delivery. The role will also own the operating models for Data Correction Requests (DCR), Master Data Management (MDM), data governance, and data warehouse platform operations. This is an operating-leadership role for someone who can provide informed direction to technical vendors while maintaining a strong focus on data quality, business requirements, operational reliability, and continuous improvement. The successful candidate will ensure that foundational data is reliable, governed, documented, and ready for use by downstream data products, analytics, and AI applications.

Requirements

Bachelor’s or Master’s degree in computer science, information systems, data management, engineering, business analytics, or a related field, or equivalent practical experience.
5+ years of experience in data management, data governance, data operations, data-platform management, or a closely related role, including ownership of complex enterprise data processes.
Demonstrated experience leading DCR, data-issue management, or comparable controlled data-change processes involving multiple business and technical stakeholders.
Strong knowledge of MDM concepts and operating practices, including identity resolution, matching and survivorship, reference data, hierarchy management, exception handling, and data stewardship.
Experience directing external vendors that perform data operations or technical delivery, including setting requirements, making implementation decisions, managing service levels, reviewing deliverables, and resolving escalations.
Experience designing or improving data-governance and data-quality processes, including ownership models, business definitions, controls, lineage, access management, and issue remediation.
Experience overseeing Snowflake or a comparable cloud data warehouse, with an understanding of platform access, security, monitoring, performance, reliability, and cost management.
Sufficient technical fluency in SQL, data models, integration patterns, and warehouse architecture to assess issues, validate vendor recommendations, and make informed decisions; hands-on engineering is not the primary focus of the role.
Pharmaceutical, biotechnology, or healthcare commercial-data experience strongly preferred, including familiarity with HCP/HCO, CRM, claims, sales and distribution, Specialty Pharmacy/HUB, payer/access, or related data.
Demonstrated success improving operational processes through clearer decision rights, standardized workflows, measurable service levels, root-cause analysis, and appropriate automation.
Excellent communication and stakeholder-management skills, with the ability to translate business requirements into clear direction for technical teams and external vendors.
Strong judgment, ownership, attention to detail, and comfort making decisions in a fast-moving, vendor-supported environment.

Nice To Haves

Pharmaceutical, biotechnology, or healthcare commercial-data experience strongly preferred, including familiarity with HCP/HCO, CRM, claims, sales and distribution, Specialty Pharmacy/HUB, payer/access, or related data.

Responsibilities

Oversee the end-to-end data-ingestion lifecycle, including source assessment, onboarding, prioritization, requirements definition, data mapping, delivery cadence, validation, production approval, and operational handoff.
Direct external vendors responsible for designing, building, testing, deploying, and operating ETL pipelines that bring internal and third-party data into data warehouse.
Translate business and downstream data needs into clear ingestion requirements, technical specifications, data contracts, quality controls, and acceptance criteria for vendor execution.
Review vendor-proposed pipeline designs, source-to-target mappings, transformation logic, test results, and implementation plans to ensure alignment with internal architecture, security, quality, and maintainability standards.
Manage vendor delivery against approved scope, timelines, service levels, cost expectations, and quality standards; resolve delivery issues and escalate material risks when necessary.
Monitor data freshness, completeness, accuracy, and pipeline reliability, and coordinate incident response, root-cause analysis, remediation, and stakeholder communication when issues arise.
Establish clear ownership, controls, and handoffs among source-system owners, external data providers, ingestion vendors, and downstream data-product teams.
Own the Data Correction Request process, including intake, triage, impact assessment, prioritization, approvals, vendor direction, validation, communication, and closure.
Lead MDM processes across key business domains, including identity resolution, matching and survivorship rules, reference data, HCP/HCO hierarchies, exception management, and data-stewardship workflows.
Serve as the accountable internal decision-maker for vendor-executed ingestion, DCR, and MDM activities, providing clear guidance on business rules, priorities, implementation decisions, and expected outcomes.
Improve ingestion, DCR, and MDM processes by addressing recurring issues, simplifying workflows, strengthening preventive controls, standardizing documentation, and introducing appropriate automation and performance metrics.
Establish and maintain data-governance standards covering data ownership, stewardship, business definitions, data quality, lineage, access, retention, and privacy-conscious data handling.
Oversee the operational governance of the Snowflake environment, including access management, monitoring, performance, cost and usage oversight, and coordination of platform changes with IT, Security, and external vendors.
Partner with the Manager, Data Product Engineering to ensure that ingested, foundational, and master data meet the requirements of downstream analytics, integrated data products, business rules, and AI applications.
Maintain documentation and reporting covering data sources, ingestion processes, lineage, vendor responsibilities, service levels, data-quality trends, pipeline reliability, platform health, and material operational risks.