Senior Specialist, Data Architect

Merck; Województwo mazowieckie; On-site; PLN 900,000 - 1,500,000; Full time

Job summary

Merck is seeking a Senior Specialist, Data Architect, GDMS Data Integration and Automation to lead design, integration, and maintenance of clinical databases and operations systems. The role requires ensuring SOPs, audits, and SLAs, mentoring teams, and providing SME support in training and cross-functional projects.

Responsibilities include designing EDC/RTSM/eCOA data solutions, implementing complex data logic, and building automated data pipelines with robust validation and reporting

Qualifications

• Proficiency in SQL, Python, SAS and R for data processing and reporting.
• Experience with data integration across clinical systems and platforms.
• Strong understanding of regulated environments and QA procedures.
• Familiarity with automation to streamline data workflows.

Responsibilities

• Design and deploy clinical technology system solutions (EDC, RTSM, eCOA/ePRO).
• Implement and validate complex data logic with scripting and validation frameworks.
• Develop advanced reporting solutions and dashboards with access controls.
• Define and optimize data integration architecture across systems.

Skills

SQL

Python

SAS

R

Data integration

Cloud computing

Regulated environments

Automation

Job description

Job Description

The Senior Specialist, Data Architect, GDMS Data Integration and Automation leads and/or executes the build, integration, and maintenance of clinical databases/clinical operational systems. In addition, the Senior Specialist, Data Architect enables clinical study systems setup, transformations, and data-integration activities across systems while enforcing enterprise standards. The Senior Specialist, Data Architect manages escalations and dependencies, ensures SLAs (Service Level Agreements) and audit readiness, guides resourcing, mentors teams, maintains SOPs/WIs (Standard Operating Procedures/ Work Instruction), and provides subject matter expertise support on training.

Responsibilities

Programming and reporting

• Design and deploy clinical technology system solutions (e.g., for EDC [Electronic Data Capture], RTSM [Randomization & Trial Supply Management], eCOA/ePRO [electronic Clinical Outcome Assessment/ electronic Patient-Reported Outcome]) using programming / reporting frameworks and automation tools.
• Implement and validate complex data logic (edit checks, derivations, dynamic rules) with fit-for-purpose scripting and validation frameworks.
• Recommend and implement tools to streamline design, build, and validation processes.
• Act as a domain expert, providing technical guidance and reviews to peers and stakeholders.
• Apply data literacy to design transformation strategies for actionable insights.
• Develop advanced reporting solutions (dashboards, listings, visual analytics) with reusable components and role-based access.

Data Engineering

• Define and optimize integration architecture, including data sources and transformation workflows across systems.
• Monitor and troubleshoot data ingestion and consumption to improve reliability.
• Automate and strengthen data engineering processes for efficiency and risk reduction.
• Collaborate with stakeholders to translate business needs into data and system requirements.
• Develop robust data models, semantic layers, and curated datasets; monitor pipelines and enforce quality checks.

Process

• Validate system functionality and ensure compliance with SOPs (Standard Operating Procedures) and regulations.
• Set documentation standards and identify process gaps for improvement.
• Lead testing strategies for solutions; automate validation and ensure traceability from requirements to evidence.
• Lead or participate in process improvement initiatives and cross-functional projects.
• Mentor junior colleagues, share best practices, and support onboarding and training.
• Lead or support release processes for various business needs across environments (data management/clinical operations), including change control and risk assessment.
• Align stakeholders by translating requirements into technical specs; lead UAT (User Acceptance Testing), capture feedback, and improve reporting standards.
• Partner across teams to turn data and technical findings into clear, actionable stories.
• Act as a reliable partner to GDMS (Global Data Management & Standards) and other cross-functional teams, actively seeking input, aligning priorities, and closing feedback loops to drive high-quality, coordinated delivery.

Technical skills

• Expert-level proficiency in various languages including SQL, Python, SAS, and R for implementing clinical data collectors, integrations, transformations, reporting and visualizations
• Experienced in the interoperability of EDC platforms, data integration environments, clinical operations systems, and cloud computing platforms
• Advanced understanding of requirements, testing, validation, and change control in a regulated environment, and how these apply to data-management tools and clinical operations solutions.
• Deep understanding of clinical data lifecycles-from design and collection through cleaning, integration, and reporting-and how these activities support trial delivery and regulatory submissions.
• Proficiency and ability to contribute in System Development Lifecycle Management / system validation activities
• Strong knowledge of common clinical and regulatory data standards, clinical operational data models and the ability to design or review data structures, mappings, and controls that are consistent and reusable.
• Experience leveraging automation, scripting, or digital solutions to streamline data-management activities and reduce manual effort.
• Knowledgeable drug discovery process, FDA regulations, GxP/ ICH (International Council for Harmonization) guidelines
• Ability to connect business outcomes to technical deliverables

Soft skills

• Communicate and negotiate effectively (oral/written) with technical and business partners and external service providers; adapt style to audience and able to translate technical topics for non-technical stakeholders.
• Lead day-to-day activities; drive issue triage to closure; coordinate stakeholders.
• Mentor junior team members on tools, checks, documentation quality, and best practices.
• Prioritize independently; r