[Hiring] Technical Data Engineering Manager @Cyntegrity

Role Description

We are looking for a Technical Data Engineering Manager to join our R&D team. This is a technically driven role at the intersection of data engineering, clinical study delivery, and customer requirements. You will play a key role in translating business and study needs into clear technical requirements, supporting Data Engineers in delivering high-quality data workflows, troubleshooting complex data issues, and contributing to scalable data solutions across our products and clinical studies.

You will work closely with Data Engineering, Project Management, Science, Product, and R&D teams, while also participating in customer discussions and helping bridge the gap between business requirements and technical implementation.

Key Responsibilities

• Translate Requirements: Turn customer and study requirements into clear technical tasks, specifications, and acceptance criteria for Data Engineering and R&D teams.
• Drive Data Delivery: Oversee the creation, transformation, mapping, and validation of datasets across clinical studies and platform components.
• Support Technical Solutions: Review data flows, mapping logic, database queries, data quality, and performance, and help troubleshoot complex data issues.
• Coordinate Across Teams: Act as a technical bridge between customers, Project Management, Data Engineering, Science, Product, and R&D.
• Improve Data Workflows: Contribute to scalable data architecture, reusable components, validation approaches, and technical best practices.
• Guide the Team: Support onboarding and capability development of Data Engineers, provide technical guidance, and help establish clear goals and ways of working.
• Manage Risks & Delivery: Track technical progress, risks, dependencies, and blockers and ensure timely escalation where needed.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or another relevant technical field.
• Additional training or experience in data management or clinical research is a plus.

Requirements

• 2+ years of relevant professional experience in data engineering, data management, software/data development, or a related technical field.
• Strong experience working with data pipelines, data transformation, integration, mapping, and data-quality processes.
• Experience translating business or customer requirements into technical solutions and developer-ready tasks.
• Experience working cross-functionally with technical and non-technical stakeholders.
• Experience coordinating or technically guiding engineers or other technical specialists.
• Experience working directly with customers or external stakeholders is highly valued.

Skills & Knowledge

• Strong working knowledge of SQL and NoSQL databases.
• Good understanding of ETL/data-processing pipelines, data mapping, validation, and performance optimization.
• Experience with data formats such as CSV, XML, JSON, SAS, and ideally clinical data standards such as CDISC.
• Understanding of common data integration methods, including APIs, SFTP, Azure Storage, and AWS S3.
• Scripting experience with Python, Node.js, C#, or similar is an advantage.
• Good analytical and problem-solving skills, with an understanding of data-processing complexity and scalability.
• Basic understanding of statistics and their application in medical research.
• Experience with LLMs and prompt engineering.
• Strong written and verbal English communication skills, with the ability to clearly document requirements, decisions, and technical discussions.

Nice to Have

• Knowledge of clinical trials, RBQM, GCP, ICH E6/E8, and 21 CFR Part 11.
• Experience with SaaS products or data-intensive software platforms.
• Product management or Business Analysis experience, including requirements elicitation, user stories, functional specifications, and acceptance criteria.
• Experience collaborating closely with engineering teams throughout product or study development.
• Knowledge of Microsoft Azure, AWS, DevOps, or cloud-based data architectures.
• Experience using AI/LLM tools to support data engineering, requirements analysis, or technical workflows.

Benefits

• A purpose-driven mission to improve global clinical research.
• A collaborative, international team that values flexibility, autonomy, and transparency.
• Fully remote work setup with a results-driven culture.
• The opportunity to work at the intersection of data engineering, clinical research, SaaS technology, and AI.
• Opportunities for professional growth and development.