Team Leader - Data Engineering (Shared Infrastructure)

Details

Bloomberg's products are fueled by powerful information. The Data organization delivers data, news, and analytics through innovative technology, applying problem-solving skills to improve workflows and implementing technology solutions that enhance systems, products, and processes.

The Data AI group brings innovative AI technologies into the Data organization while contributing financial domain expertise to AI-powered products. The group partners with stakeholders to align AI innovation with Bloomberg's strategic objectives, optimize data workflows, and improve the quality, intelligence, and usability of the data that drives Bloomberg's products.

The Team Leader will drive Shared Infrastructure programs within Data, enabling scalable and responsible data workflows through reusable infrastructure, integration patterns, and operational standards. The role partners with Engineering, Product, and Data teams to identify high-impact opportunities, define and implement reusable solutions, and enable consistent workflows across distributed teams. Responsibilities include shaping the adoption and production integration of automated evaluation and LLM-enabled annotation capabilities in collaboration with teams that own the underlying platforms.

Responsibilities

• Lead and develop a central team responsible for shared data infrastructure and reusable workflow patterns that improve consistency and efficiency across teams.
• Provide technical and strategic leadership by translating diverse team needs into requirements, scalable solutions, and approaches to data workflows, automated evaluation, and efficient annotation.
• Partner with Engineering, Product, and Data leaders to identify opportunities for shared capabilities, align priorities, and ensure solutions can be put into production within technical, compliance, and cost constraints.
• Coordinate cross-team needs, identify common gaps, reduce duplication, and enable consistent approaches without becoming a bottleneck or enforcement layer.
• Ensure shared components, frameworks, and patterns are well-designed, documented, usable, scalable, and broadly adopted.
• Mentor and develop data engineers while promoting pragmatism, strong technical judgment, and scalable, widely usable solutions.

Requirements

• Prior people leadership experience, ideally guiding teams working on technical, data, or infrastructure-related problems in multifunctional environments.
• Strong technical judgment in data engineering and shared systems design, including the ability to engage with engineering partners on architecture, trade-offs, and scalable solutions.
• Experience designing and scaling shared frameworks, systems, or platform-like capabilities across multiple teams.
• Experience with LLM-enabled workflows or annotation pipelines.
• Ability to operate in ambiguous, high-judgment environments and translate diverse needs into clear requirements and practical, scalable solutions.
• Proven ability to drive alignment and influence partners across engineering, product, and data teams without direct authority.
• Strong analytical and decision-making skills, with a track record of delivering clear, well-reasoned, and impactful solutions.

Preferred Qualifications

• Familiarity with evaluation or data quality frameworks.
• Exposure to regulated or cost-constrained environments.
• Experience partnering with engineering teams to scale prototypes into production.
• Background in platform, infrastructure, or centralized enablement teams.
• Experience contributing to communities of practice or developer enablement efforts.

Benefits

Benefits and total rewards may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental and vision coverage, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs. Benefits are not provided directly to contingent workers, contractors, or interns.