We're seeking a
Senior Manager of Engineering Data Products
to accelerate the
AI transformation of Clarivate's 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 Clarivate's 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.
- Bachelor's or master's 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
At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.
