Senior Manager, Data Engineering

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Manager, Data Engineering based in the United States. The Senior Manager, Data Engineering will lead the development of a modern data platform that makes trusted, governed information accessible to product teams, business stakeholders, and AI agents. This player-coach role combines strategic leadership with hands‑on technical expertise, shaping architecture while guiding a team of skilled data engineers.

You will build reliable data pipelines, consistent metrics, and secure APIs that connect information across the entire customer journey. Working closely with Finance, Operations, Sales, Marketing, and Product, you will translate evolving business needs into scalable data solutions. You will also advance AI-enabled engineering practices and ensure that data consumed by AI systems remains traceable, secure, and reliable. This is an opportunity to influence the organization’s data strategy while developing people, improving operational efficiency, and enabling better business decisions.

• Lead and develop the team:
  Recruit, coach, and retain talented data engineers. Set clear expectations, provide constructive feedback, establish career development paths, and build a collaborative team that can operate effectively without relying on individual contributors.
• Define the roadmap and deliver results:
  Translate business objectives into a prioritized data engineering roadmap, communicate trade-offs, establish delivery expectations, and lead cross-functional initiatives on time and within budget.
• Own data architecture:
  Establish and evolve the architecture for data ingestion, warehousing, modeling, semantic layers, lineage, and governance. Lead architecture reviews, maintain technical standards, and contribute directly to implementation when needed.
• Build reliable data pipelines:
  Ensure data pipelines meet defined service-level agreements, maintain consistent metric definitions, and provide dependable information for reporting, products, and AI-powered applications.
• Develop secure data access capabilities:
  Oversee the design and implementation of the platform’s serving layer and APIs, establishing standards for authorization, access control, privacy, and the secure handling of personally identifiable information.
• Prepare data for AI agents:
  Build governed, agent‑ready data capabilities that allow AI systems to retrieve trustworthy information and produce answers that can be traced back to their original sources.
• Advance agentic engineering practices:
  Use coding agents in your own engineering workflow and introduce effective agentic development practices across the team to improve productivity and delivery.
• Manage vendors and costs:
  Evaluate data platform providers and engineering tools, negotiate contracts within delegated approval limits, and monitor warehouse and tooling expenses to maintain cost efficiency.
• Partner across business functions:
  Collaborate with Finance, Operations, Sales, Marketing, Product, Accounting, and Capital Markets stakeholders to understand data needs, build consensus, and recommend practical solutions.
• Drive continuous improvement:
  Balance technical quality, delivery speed, cost, and business impact while making deliberate decisions about priorities and determining which initiatives should not be pursued.

• Professional experience:
  At least 10 years of experience in software engineering or data engineering, including 5 or more years managing engineers.
• People leadership: A proven record of recruiting strong engineers, developing talent, building effective teams, and establishing clear accountability and career growth…