Senior Manager Data and Analytics (2504)
Pivotal Talent Search
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New York, NY · Posted September 30, 2026
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Where New York, NY ranks
Where New York, NY placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for operations jobs1,429 openings · of 100
- #1Best cities for sales jobs2,774 openings · of 78
- #1Best cities for finance jobs1,932 openings · of 78
- #1Best cities for data and analytics jobs1,713 openings · of 58
- #1Best cities for HR jobs994 openings · of 30
- #1Best cities for marketing jobs1,754 openings · of 31
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
Data & Analytics jobs · Top Data & Analytics employers · All rankings
How AI is used in this kind of work
Among database architects, AI is already used for a large share of the tasks. Measured exposure for database architects: 58% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
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About the job
THE ROLE
A confidential, highly respected, multi-billion-dollar global retailer is seeking a Senior Manager, Data & Analytics to help lead the continued evolution of its enterprise Data & Analytics platform.
This high-impact leadership role will lead a global Data Engineering team while helping shape the architecture, strategy, and modernization of a sophisticated enterprise data environment. Working across Microsoft Azure, Snowflake, Databricks, Confluent Kafka, and Power BI, this leader will drive scalable Data Platform capabilities that support Analytics, Business Intelligence, Data Science, AI, Data Sharing, and API use cases across the organization.
The ideal candidate brings deep technical expertise in modern Data Architecture along with proven leadership experience. This person has successfully built and modernized enterprise Data Platforms, understands Data Lake and Lakehouse architecture, batch and streaming pipelines, event-driven architecture, ETL/ELT, and dimensional modeling, and can influence technical direction while developing strong teams and driving execution.
RESPONSIBILITIES
Lead a global Data Engineering team responsible for enterprise Data Platforms, engineering, and day-to-day data operations
Help define and execute the Data Platform strategy, architecture, roadmap, and modernization priorities across the organization
Design scalable Data Architecture leveraging Microsoft Azure, Snowflake, Databricks, and Kafka to support batch and streaming data pipelines
Build and evolve enterprise Data Lake and Lakehouse architecture, reusable components, frameworks, and engineering standards
Lead enterprise canonical and dimensional data modeling to support descriptive, diagnostic, exploratory, and predictive analytics
Partner across Data Engineering, Business Intelligence, Data Architecture, Data Science, Product, Technology, and business teams to deliver scalable data capabilities
Drive architectural and engineering best practices across operational excellence, security, reliability, performance, metadata management, and cost optimization
Support the full technology lifecycle from architecture and requirements through development, integration, deployment, operations, maintenance, and modernization
Influence Architects and Engineers across the organization while establishing standards and driving alignment around modern Data & Analytics architecture
Mentor and develop team members while creating a culture of technical excellence, accountability, collaboration, and continuous improvement
Ensure platform stability, business continuity, risk mitigation, and successful delivery of critical Data & Analytics initiatives
IDEAL BACKGROUND
12+ years of experience across Data Architecture, Data Engineering, dimensional modeling, data ingestion, and transformation design
5+ years working within public cloud environments with significant focus on Data Architecture and Big Data technologies
Deep implementation experience with Snowflake and Databricks, including modern Data Architecture, data pipelines, and capabilities supporting Analytics, BI, Data Science, and AI
Strong experience designing and implementing Data Lake and Lakehouse architecture patterns
Experience with event-driven architecture, Kafka, batch and streaming pipelines, ETL, and ELT
Strong understanding of Master Data Management, Reference Data Management, and Metadata Management
Demonstrated experience building scalable enterprise data frameworks, architecture standards, and reusable engineering capabilities
Proven leadership experience managing and developing Data Engineering teams, ideally within a global or highly complex organization
Ability to remain technically credible while influencing Architects, Engineers, Product teams, business partners, and senior stakeholders
Strong understanding of platform reliability, security, performance, operational excellence, and cost optimization
Public cloud experience with Microsoft Azure strongly preferred; AWS or Google Cloud experience also relevant
Bachelor's degree in Computer Science or a related field
Retail, Fortune 500, and Agile/Scrum experience preferred
WHY THIS ROLE
This is an opportunity to play a meaningful role in the continued modernization of Data & Analytics for a large, complex global organization.
The successful leader will have the opportunity to shape enterprise Data Platform strategy, modernize architecture, lead a global engineering team, and build scalable capabilities that enable Analytics, Data Science, and AI across the business. It’s an ideal opportunity for someone who enjoys staying close to the technology while also having the leadership scope and influence to determine where the organization goes next.