Data Quality Assurance Squad Lead

Remote, EuropeRemote

About

he ADE ASM Converter Development and Data Quality Assurance Squad Lead is responsible for leading the end-to-end delivery of ASM converters by driving requirements gathering, semantic modeling, validation, release readiness, and deployment activities. Partner with Scientists, SMEs, Semantic Engineers, vendors, and cross-functional teams to define converter requirements, align Allotrope schema and ontology mappings, and ensure delivery of compliant, high-quality ASM solutions. Oversee validation strategy, test automation, SDLC documentation, data integrity, and regulatory compliance while providing leadership to the validation squad, managing project risks and dependencies, and driving continuous improvement, standardization, and adoption of best practices across the ASM converter lifecycle.

Requirements

Define converter scope, validation strategy, acceptance criteria, test scenarios, and release readiness requirements for ASM converter onboarding.
Drive alignment across Scientific, ADE, Quality Engineering, Product, and Vendor teams to ensure successful converter onboarding, validation, and release readiness.
Ensure delivered ASM converters meet scientific, technical, quality, compliance, and business objectives.
Provide leadership and mentorship to team members while promoting best practices in ASM, Allotrope standards, semantic modeling, validation methodologies, and scientific data quality.
Lead continuous improvement initiatives focused on converter quality, validation efficiency, documentation standards, process standardization, and reusable validation assets.
Promote risk-based decision-making and quality-focused delivery throughout the ASM converter lifecycle.
Ensure adherence to Merck Quality Engineering, SDLC, data governance, and compliance requirements.

Day-to-Day Responsibilities

Lead requirements for instrument data gathering, discovery, and working sessions with Scientists, SMEs, and stakeholders to define converter scope, Merck Key Fields, and scientific requirements.
Collaborate with ADE Semantic Engineers and vendor teams to map instrument data to Allotrope Ontology and define required semantic mappings and schema extensions.
Coordinate converter development activities with vendors and technical teams to ensure alignment with scientific, business, and quality requirements.
Lead pre-validation activities, including sample data reviews, semantic mapping validation, dry-run ASM assessments, and converter output verification.
Lead and provide oversight to the Quality Engineering squad performing source-to-target validation, data transformation verification, traceability testing, and converter quality assessments.
Review validation results, test evidence, defects, and quality metrics to support delivery and release readiness.
Lead defect triage, issue resolution, risk assessments, and remediation planning throughout the converter lifecycle.
Coordinate validation governance activities, including test reviews, approval workflows, Jira traceability, audit readiness, and release sign-offs.
Author and review SDLC documentation, mapping specifications, lifecycle documents, and validation artifacts.
Partner with Delivery Orchestrators, Product Owners, Business Leads, and stakeholders to communicate status, manage dependencies, and resolve delivery risks and issues.

Required Skills & Experience

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Information Systems, Biotechnology, or related fields, or equivalent professional experience.

8+ years of experience as a Product Analyst, preferably in the pharmaceutical industry.

Strong knowledge of data modeling, data mapping, data transformation, data quality, and traceability concepts.

Strong understanding of DPTM and DSCS domains.

Experience in data quality assurance: defining solution scope, requirements, acceptance criteria, validation approaches, and test scenarios based on business and data requirements.

Knowledge of laboratory systems (LIMS, Signals, lab instruments) and pilot plant/manufacturing systems (PI, Delta-V, SIPAT, MES).

Proficiency in SQL, Python/R, Excel, Power BI, and cloud platforms such as AWS.

Understanding of the software lifecycle, data lifecycle management, and data governance principles.

Experience partnering with non-technical stakeholders (business or science) to translate requirements into scalable data solutions.

Strong domain knowledge of drug discovery and drug development processes.

Demonstrated ability to manage and document risks, issues, dependencies, decisions, and stakeholder expectations throughout project delivery.

Proven leadership experience coordinating small technical teams, prioritising work, removing blockers, and driving execution against project milestones.

Experience collaborating with cross-functional teams including Business, Scientific SMEs, Engineering, Quality, Product, Architecture, and external vendors.

Nice to Have

Experience with the pharmaceutical industry and drug discovery process; understanding of scientific data and laboratory workflows.

Proven experience leading data onboarding, integration, validation, migration, or transformation initiatives in complex business environments.

Prior experience with Allotrope data schemas (especially Allotrope Simple Model), Jira, VERA/XRAY, Confluence, Mural, and automated validation testing tools.

Start

Immediate2 weeks notice

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