Sr. Manager, Data Engineering & Applied Data Science
About The Position
The Senior Manager – Data Engineering & Applied Data Science leads the strategy, design, and delivery of enterprise data products, applied data science, and AI solutions that support business growth and digital transformation. The role leads a multidisciplinary Data Engineering and Applied Data Science team, translating business challenges into scalable, production-ready data and AI products. The successful candidate combines technical leadership and business acumen to build AI-ready data foundations, develop advanced analytics and machine learning solutions, and evolve capabilities using emerging technologies and engineering best practices. The role ensures enterprise data is standardized, contextualized, governed, and optimized for analytics, machine learning, and Generative AI. The position leads data and AI solution delivery; establishes data engineering standards for reliable, secure, scalable pipelines and products; guides production deployment of machine learning, Generative AI, and advanced analytics; and ensures data products are trusted, governed, and accessible. It also shapes technology roadmaps, evaluates emerging technologies and architectural patterns, develops high-performing teams, and partners with business, architecture, platform, security, and technology functions. The role may require travel up to 20% as needed.
Requirements
- Advanced degree plus 6 years of experience, or bachelor's degree plus 8 years of experience in data science and analytics leadership roles.
- Strong expertise in machine learning, AI, and statistical modeling techniques.
- Advanced proficiency in Python, R, and SQL.
- Experience with TensorFlow, PyTorch, and scikit-learn.
- Demonstrated success leading and mentoring data science teams.
- Expertise in data visualization tools such as Tableau and Power BI, and BI platforms.
- Proven track record of implementing large-scale data science solutions.
- Experience with cloud platforms such as AWS, Azure, or GCP, and big data technologies.
- Strong knowledge of data governance and regulatory compliance.
- Excellent project management and cross-functional collaboration skills.
- Outstanding communication abilities to translate technical concepts for diverse audiences.
- Experience with Agile/Scrum methodologies.
- Proven ability to deliver business results through data-driven insights.
- Experience with automation tools and process optimization.
- Strong problem-solving and analytical thinking capabilities.
Nice To Haves
- Preferred fields of study: Data Science, Computer Science, Statistics, Mathematics, Analytics, or a related field.
- Advanced certifications in data science, machine learning, or AI technologies are valued.
Responsibilities
- Translate business priorities into scalable enterprise data products, advanced analytics, machine learning, and AI solutions that deliver measurable business value.
- Lead the design and delivery of reliable, secure, and scalable data pipelines and products, establishing standards for DataOps, CI/CD, automation, observability, and cloud-native development.
- Guide the development and production deployment of machine learning, Generative AI, and advanced analytics solutions, including reusable frameworks and scalable AI capabilities.
- Ensure enterprise data products are trusted, governed, contextualized, and optimized for analytics and AI through data quality, metadata, lineage, semantic models, and accessibility.
- Develop technology roadmaps and evaluate emerging technologies and architectural patterns to accelerate AI adoption, improve engineering productivity, and strengthen enterprise data capabilities.
- Build and develop high-performing Data Engineering and Applied Data Science teams.
- Partner across business, architecture, platform, security, and technology functions to align priorities, communicate outcomes, and drive execution.
- Mentor data science teams and deliver business results through data-driven insights.
- Travel up to 20% as needed.
Benefits
- Choice of national medical and dental plans and a national vision plan, including health incentive programs.
- Employee assistance and family support programs, including commuter benefits and tuition reimbursement.
- At least 120 hours of paid time off (PTO) and 10 paid holidays annually.
- Paid parental leave: 3 weeks for bonding and 8 weeks for caregiver leave.
- Accident and life insurance, and short- and long-term disability in accordance with company policy.
- Competitive 401(k) U.S. retirement savings plan.
- Employees’ Stock Purchase Plan (ESPP), offering eligible colleagues the opportunity to purchase company stock at a discount.
- May be eligible for a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
