Data Engineering Manager, Commercial US
Sanofi
August 20, 2026
On-site
Morristown, NJ
$148,500 - $214,500 USD yearly
IT
Main Responsibilities:
- Lead, mentor, and develop a team of data engineers; foster quality, accountability, collaboration, and continuous improvement.
- Design, build, deploy, and support scalable data pipelines and data products for analytics, AI/ML, and commercial use cases.
- Lead discovery, solution design, and technical planning with business, analytics, AI, and technology teams.
- Manage delivery, priorities, capacity planning, and execution across concurrent initiatives.
- Design/test/optimize reusable data engineering solutions and assets for business-critical global workflows.
- Provide architectural leadership across orchestration, distributed processing, cloud-native platforms, and data integration patterns.
- Ensure operational excellence for production data assets (monitoring, troubleshooting, incident response, release management).
- Identify opportunities to automate/simplify/standardize/optimize processes and platform capabilities.
- Collaborate in cross-functional agile teams; evolve engineering standards and best practices; stay current with emerging technologies.
Qualifications:
- 6+ years data engineering/analytics engineering/platform development; 2+ years leading/managing engineering teams.
- Experience building/operating scalable pipelines/platforms (e.g., Spark, Kafka, Snowflake, Hadoop or similar).
- Cloud-native data engineering and modern ETL/ELT (prefer Snowflake/AWS); Informatica/IICS preferred.
- Advanced SQL/data modeling; Python scripting; Scala/Java a plus.
- Batch/near real-time/streaming architectures; data warehouse/lake/lakehouse and data mesh concepts.
- Strong stakeholder management and ability to translate ambiguous needs into scalable solutions.
- Agile delivery experience (CI/CD, release management, testing, operational support).
- Bachelor’s/Master’s in CS/Engineering/STEM/Business or equivalent.
Nice to Haves:
- Life sciences/healthcare/pharma experience; Airflow/dbt (or similar); data governance/quality and commercial domains; vendor and offshore/onshore models.
Benefits (as stated):
- Rewards package; healthcare and prevention/wellbeing programs; at least 14 weeks’ gender-neutral parental leave.
- Lead, mentor, and develop a team of data engineers; foster quality, accountability, collaboration, and continuous improvement.
- Design, build, deploy, and support scalable data pipelines and data products for analytics, AI/ML, and commercial use cases.
- Lead discovery, solution design, and technical planning with business, analytics, AI, and technology teams.
- Manage delivery, priorities, capacity planning, and execution across concurrent initiatives.
- Design/test/optimize reusable data engineering solutions and assets for business-critical global workflows.
- Provide architectural leadership across orchestration, distributed processing, cloud-native platforms, and data integration patterns.
- Ensure operational excellence for production data assets (monitoring, troubleshooting, incident response, release management).
- Identify opportunities to automate/simplify/standardize/optimize processes and platform capabilities.
- Collaborate in cross-functional agile teams; evolve engineering standards and best practices; stay current with emerging technologies.
Qualifications:
- 6+ years data engineering/analytics engineering/platform development; 2+ years leading/managing engineering teams.
- Experience building/operating scalable pipelines/platforms (e.g., Spark, Kafka, Snowflake, Hadoop or similar).
- Cloud-native data engineering and modern ETL/ELT (prefer Snowflake/AWS); Informatica/IICS preferred.
- Advanced SQL/data modeling; Python scripting; Scala/Java a plus.
- Batch/near real-time/streaming architectures; data warehouse/lake/lakehouse and data mesh concepts.
- Strong stakeholder management and ability to translate ambiguous needs into scalable solutions.
- Agile delivery experience (CI/CD, release management, testing, operational support).
- Bachelor’s/Master’s in CS/Engineering/STEM/Business or equivalent.
Nice to Haves:
- Life sciences/healthcare/pharma experience; Airflow/dbt (or similar); data governance/quality and commercial domains; vendor and offshore/onshore models.
Benefits (as stated):
- Rewards package; healthcare and prevention/wellbeing programs; at least 14 weeks’ gender-neutral parental leave.