Senior Manager, Data Engineering

Responsibilities:

• Leads and develops a team of managers, technical leads, and engineers, building a strong leadership bench and high-performing engineering culture while setting performance standards, coaching, and supporting career development.
• Owns the end-to-end lifecycle of enterprise data products and platforms, including definition, development, delivery, and optimization, ensuring scalability, reuse, quality, and measurable business value.
• Directs planning, prioritization, and execution of data product roadmaps and engineering initiatives aligned to business outcomes and enterprise strategy, while driving adoption and reliability across domains.
• Leads the design and development of scalable data pipelines, platforms, and frameworks, enabling efficient data integration, self-service consumption, and insight generation from large, complex datasets.
• Establishes and enforces data quality, governance, and observability practices, ensuring data integrity, consistency, and trust across the data ecosystem.
• Partners with senior leaders and cross-functional teams to shape data strategy, influence operating models, and deliver high-impact, outcome-based solutions.
• Evaluates and implements modern data technologies and architecture patterns to improve scalability, performance, and developer experience while fostering innovation and continuous improvement.
• Participates in special projects and performs other duties as assigned.

• Minimum of ten years' business or technical experience including people management and data expertise.
• Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
• Experience leading data engineering teams and delivering scalable data solutions.
• Experience partnering with business and technical stakeholders to define requirements and deliver data solutions.
• Experience translating business needs into data engineering solutions or products.
• Proven track record delivering data initiatives in complex or ambiguous environments.
• Experience with modern data engineering technologies and cloud platforms (e.g., AWS or similar).
• Hands-on or leadership experience with data modeling, data quality, and data management practices.

• Graduate degree preferred.
• Exposure to modern data platforms (e.g., data lakes, real-time systems, Databricks).
• Familiarity with data visualization tools (e.g., Tableau, Power BI) and analytics workflows.
• Experience making decisions in ambiguous or high-stakes environments.
• Deep understanding of data and analytics principles, including data quality and modeling.
• Experience making decisions in ambiguous or high-stakes environments.
• Experience driving change and influencing adoption across teams.