Senior Manager, Analytics Engineering
Indexed description
Job Description
The Senior Manager, Analytics Engineering leads a centralized analytics engineering function responsible for delivering scalable, business-ready data solutions across multiple commercial domains.
Role
This role operates within a hybrid model - leveraging enterprise data infrastructure while enabling rapid, business-driven development within Microsoft Fabric. As a hands-on leader, this role is accountable for:
- Owning analytics data architecture and standards
- Managing delivery across a shared service model
- Leading a distributed team of Analytics Engineers
- Personally contributing to complex data and analytics solutions
Key Responsibilities
Data Architecture & Technical Ownership
- Own the design and evolution of data pipelines, transformations, and data models
- Define standards for scalable and reusable datasets
- Ensure business logic is consistently structured and reusable across reporting and analytics
- Establish a clear and maintainable “last-mile” data layer for business consumption
- Own and manage a centralized analytics engineering backlog across multiple domains
- Make prioritization and tradeoff decisions across competing business needs, balancing speed, scalability, and impact
- Establish clear intake, prioritization, and delivery processes
- Ensure consistent, high-quality, and timely execution
- Operate a global shared analytics engineering function supporting multiple business domains simultaneously
- Allocate resources effectively across competing priorities
- Act as the primary escalation point for prioritization and delivery tradeoffs
- Balance speed, scalability, and data governance in all decisions
- Oversee the conversion of Proof of Concepts into scalable, production-ready data solutions
- Enable fast iteration while progressively improving structure, performance, and reusability
- Standardize and scale business logic across datasets and reporting assets
- Personally contribute to complex data transformations, pipelines, and models
- Support debugging, optimization, and resolution of critical technical challenges
- Step in to accelerate delivery for high-priority or high-complexity work
- Lead and develop a team of Analytics Engineers operating in a distributed delivery model
- Set priorities, manage capacity, and drive accountability for delivery outcomes
- Coach team members on technical execution, data design, and delivery best practices
- Build a disciplined, high-performing execution engine
- Partner with IT to align with enterprise data architecture, standards, and governance
- Operate within enterprise guardrails while maintaining flexibility and speed
- Collaborate with Insights Managers to translate business needs into scalable data solutions
- Determine when solutions should remain business-owned vs. transition to IT for enterprise scale
- Ensure accuracy, consistency, and reliability of all data assets
- Establish validation, monitoring, and quality assurance processes
- Implement DataOps best practices including version control, structured deployment, and reusable design
- Maintain clear documentation across data pipelines, datasets, and processes
- Bachelor’s degree in computer science, engineering, business, finance, or related field
- 8–12+ years of experience in analytics engineering, data engineering, or business intelligence
- Proven experience leading teams in a global or distributed delivery model
- Deep expertise in SQL, ETL/ELT design, and data modeling
- Strong hands-on experience with Microsoft Fabric (Lakehouse, notebooks, pipelines, semantic models) or similar modern data platforms
- Demonstrated ability to work with ambiguous, incomplete, or evolving data and business requirements
- Proven ability to manage multiple stakeholders, priorities, and competing deadlines
- Strong communication skills, with the ability to translate technical concepts into business context
- Experience supporting commercial, sales, or operational analytics
- Experience working in hybrid IT + business-owned data environments
- High-quality, scalable data solutions delivered consistently across multiple domains
- Strong prioritization and effective backlog management
- Rapid delivery of business value without sacrificing long-term scalability
- Clear, maintainable, and reusable data architecture
- Effective partnership with IT without creating bottlenecks
- Insights teams enabled with reliable, business-ready datasets
- A hands-on technical leadership role
- Accountable for both delivery execution and data architecture
- Responsible for prioritization, tradeoffs, and outcomes
- A purely managerial or coordination role
- A centralized IT data engineering role
- Limited to oversight without direct technical contribution
Relocation: No
Sealed Air is committed to attracting, selecting, and developing talent that reflects the diversity of the communities and customers we serve. We take pride in our selection process to identify, infuse, and grow talent to align with our culture, values, and norms. Sealed Air prioritizes talent development, fostering a culture of continuous growth and career progression. The company is committed to providing equal employment opportunities to all applicants for employment and to all employees, without regard to race, color, religion, gender identity or expression, national origin, age, protected disability, veteran status, or any other protected status in accordance with applicable federal, state and local laws.
- Please be cautious of fraudulent recruiting efforts using the Sealed Air name or logo. Sealed Air will never request private information during the application process, such as a Driver's License or Social Security Number. If you have any concerns about information received from SEE during the application process, please reach out to us directly at [email protected].
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