2 часа назад
Data Engineering Manager (Commercial US)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineering Manager (Commercial US) (Data Platforms/AI): Building and operating scalable data pipelines, data products, and cloud-native platforms for analytics, AI/ML, and commercial use cases with an accent on distributed processing, streaming architectures, and enterprise data reliability. Focus on leading engineering delivery, designing reusable data assets, optimizing production operations, and translating ambiguous business needs into scalable technical solutions.
Location: Morristown, New Jersey, United States; hybrid work arrangement
Company
is an R&D-driven, AI-powered biopharmaceutical company developing medicines and vaccines for people worldwide.
What you will do
- Lead, mentor, and develop a team of data engineers while promoting accountability, collaboration, engineering quality, and continuous improvement.
- Design, build, deploy, and support scalable data pipelines, data platforms, and reusable data products for analytics, AI/ML, and commercial use cases.
- Provide architectural leadership across pipeline orchestration, distributed processing, cloud-native platforms, data integration, and data architecture.
- Lead discovery, solution design, technical planning, prioritization, capacity planning, and delivery across multiple concurrent initiatives.
- Drive operational excellence through monitoring, troubleshooting, incident response, release management, testing, and continuous improvement.
- Partner with data, digital, infrastructure, cloud, security, analytics, product, governance, and business stakeholders to deliver reliable enterprise data solutions.
Requirements
- 6+ years of experience in data engineering, analytics engineering, or data platform development, including 2+ years leading or managing engineering teams.
- Experience designing, building, and operating scalable pipelines, data platforms, and distributed processing solutions using technologies such as Spark, Kafka, Snowflake, Hadoop, or similar.
- Strong experience with cloud-native data engineering, modern ETL/ELT, Snowflake or AWS environments, advanced SQL, and data modeling.
- Working knowledge of Python and scripting languages; experience with batch, near real-time, and streaming architectures, data warehouses, lakes, lakehouses, and data mesh principles.
- Strong understanding of scalability, reliability, performance optimization, operational support, CI/CD, release management, and software engineering practices.
- Bachelor’s or Master’s degree in Computer Science, Engineering, STEM, Business, or a related field, or equivalent practical experience.
Nice to have
- Experience in life sciences, healthcare, or pharmaceutical industries.
- Experience with Airflow, dbt, Informatica, or IICS.
- Familiarity with data governance, data quality, and commercial data domains such as omnichannel, pricing, customer engagement, or sales analytics.
- Experience working with external vendors and offshore/onshore delivery models.
Culture & Benefits
- Supportive, future-focused environment centered on science, innovation, sustainability, and social responsibility.
- Career growth opportunities through promotions and lateral moves, including international opportunities.
- Company rewards and employee benefit programs.
- Healthcare, prevention, wellness, and family benefits, including at least 14 weeks of gender-neutral parental leave.
- Opportunity to modernize data and technology capabilities supporting a global biopharmaceutical business.
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