remoteonsite
Service Development Manager - AI Data Assurance & Validation - Elsevier
Software Engineer
Lead AI‑driven data assurance and validation initiatives, ensuring high‑quality, reliable data services for research platforms. Combine data engineering, automation, and cloud expertise to drive continuous improvement and governance across the data mesh ecosystem.
About the role
Key Responsibilities
- Design, develop, and maintain automated AI‑based data validation pipelines that ensure accuracy, completeness, and compliance of research data.
- Collaborate with data engineers, product owners, and external suppliers to define data quality standards and governance policies.
- Implement CI/CD processes and cloud infrastructure (AWS) to scale validation services and support rapid release cycles.
- Monitor data quality metrics, conduct root‑cause analysis of anomalies, and drive corrective actions across the platform.
- Mentor junior team members and promote best practices in data testing, documentation, and agile delivery.
Requirements
- 5+ years of experience in data engineering or data quality engineering, preferably in a research or scientific data environment.
- Strong programming skills in Python and proficiency with SQL for data manipulation and validation.
- Hands‑on experience with cloud platforms (AWS) and CI/CD tools (e.g., Jenkins, GitLab CI).
- Familiarity with data mesh concepts, data governance, and AI/ML techniques for automated quality checks.
- Proven ability to work in Agile teams, communicate across technical and business stakeholders, and lead data‑centric projects.
Skills
pythonsqlawscicdagile