Were seeking a Senior Manager of Engineering Data Products to accelerate the AI transformation of Clarivates Life Sciences & Healthcare (LSH) product ecosystem . With our platforms used by leading global pharma and biotech organizations, this role offers a rare opportunity to shape the next generation of AI-driven products that empower researchers, scientists, and healthcare professionals worldwide.
You will define strategy, build high-performing teams, and deliver the data foundations that infuse AI and advanced analytics across Clarivates LSH ecosystem. Leveraging your US Healthcare expertise and leadership in AI- and data-driven product engineering, you will guide teams in building scalable data platforms, delivering advanced analytics, and enabling AI/ML across the LSH portfolio. You will lead cross-functional initiatives, drive innovation, and ensure robust engineering practices to support enterprise-grade AI adoption.
About You Experience, Skills, and Accomplishments
- Minimum 10+ years in data engineering, analytics engineering, or data-intensive software engineering, with strong exposure to US Healthcare data (payer/provider ecosystems, claims, clinical, RWE datasets).
- 5+ years building AI-enabled products with strengths in data pipelines, data modeling, analytics platforms, or MLOps.
- Proven experience as a Senior Product Engineering Manager or Senior Data Engineering Manager , leading large data-focused teams and cross-functional programs.
- Familiarity with cloud-native data architectures (AWS, Azure, GCP), distributed data processing, and modern data pipelines.
- Working knowledge of SQL, Python, ETL frameworks, APIs, orchestration tools , and microservices (nice to have).
- Exposure to analytics/ML ecosystems such as Snowflake, Databricks, Spark, TensorFlow, PyTorch, MLflow .
- Experience with GenAI, LLMs, vector databases, and agentic AI is a strong plus.
- Bachelors or masters degree in Computer Science, Data Science, Engineering, Analytics , or related fields.
It would be great if you also had
- Experience with Life Sciences datasets, regulatory models, or healthcare analytics workflows is highly valued.
What will you be doing in this role?
Data Engineering & Platform Leadership
- Lead teams building scalable, secure, and efficient data pipelines powering AI-driven applications across the LSH ecosystem.
- Architect and evolve cloud-native data platforms to support analytics, ML, and real-time insight generation.
- Ensure high-quality data ingestion, transformation, modeling, and governance practices.
AI & Analytics Enablement
- Translate business and scientific requirements into data engineering and analytics solutions that drive measurable impact.
- Partner with data scientists and ML engineers to operationalize AI/ML models within production pipelines.
- Enable advanced analytics by delivering well-structured, performant, and compliant datasets.
Data Quality, Compliance & Security
- Embed healthcare-grade compliance , governance, and data security into engineering processes.
- Ensure reliability, observability, and auditability across all data workflows.
Innovation & Emerging Technologies
- Introduce modern data engineering and analytics technologies, including GenAI, automated ETL, real-time streaming, and emerging data tools.
- Guide teams through experimentation, rapid prototyping, and adoption of innovative AI/analytics capabilities.
Leadership & Operational Excellence
- Manage, mentor, and grow data engineers, analytics engineers, and technical leads.
- Drive operational excellence in sprint execution, delivery management, and cross-team coordination.
- Lead hiring, coaching, and performance management to cultivate high-performing, scalable teams.
Cross-Functional Collaboration
- Partner with product, engineering, data science, architecture, and business teams to align priorities with product goals.
- Communicate progress, insights, risks, and roadmap alignment to senior leadership.
- Influence enterprise-wide strategies for data standards, analytics platforms, and AI readiness.
About the Team
You will be part of the LSH Commercial Technology Product Engineering organization, owning delivery across data- and AI-focused product features . The team is globally distributed across India and the U.S., working collaboratively in a hybrid model.
Hours of Work
- Full-time
- 45 hours per week
- Hybrid working model
