Team Leader - Process Engineering

Details

Bloomberg runs on data, and in the Data department, we are responsible for acquiring, interpreting, and supplying data insights to our clients. Our Data teams work to collect, analyze, process, and publish the data which is the backbone of our iconic Bloomberg Terminal — the data which ultimately moves the financial markets. We’re responsible for delivering this data, news, and analytics through innovative technology — quickly and accurately.

Team overview

The Data Management Lab (DML) sits within the Data organization and supports Data’s pursuit of data management excellence by aligning industry best practices with Bloomberg's established expertise in financial market data. DML empowers our data professionals to make their products “ready-to-use,” through promoting increased data discoverability, accessibility, appraisability, interoperability, and analysis-readiness.

As a core component of the Quality Methods & Insights (QMI) group, the Process Engineering (PE) team supports the design and optimization of operational processes for our data manufacturing pipelines. We are passionate about how our people and technology work in concert, leveraging a suite of powerful tools built by infrastructure engineers. In partnership with Data Quality and Business Intelligence, we advance the Data Management Lab's mission by empowering data teams with advances in observability, instrumentation, and analysis to meet the evolving needs of Bloomberg's clients.

We are undergoing a strategic evolution, transitioning from a tactical implementation focus to a strategic enablement and empowerment role. We are seeking a visionary leader to manage our multi-disciplinary Process Engineering team, which includes Industrial Engineers and Process Systems Specialists.

Responsibilities

• Set the strategic vision for process excellence across data manufacturing pipelines; define the team's roadmap and operating models to drive collaboration with engineering, data, and product teams.
• Build and manage a strategic portfolio of process improvement initiatives; prioritize efforts using systematic frameworks to align projects with business goals (improved product quality, risk management, operational efficiency).
• Lead and mentor a team of specialists in Industrial Engineering and Process Engineering, fostering innovation, methodological rigor, and shared ownership.
• Collaborate closely with Data Quality and Business Intelligence to create unified approaches to process design, observability, instrumentation, and analysis-readiness.
• Oversee deep-dive investigations to identify bottlenecks and inefficiencies; quantify opportunities using advanced Industrial Engineering and Operations Research methodologies and champion AI-driven automation or process redesign.
• Guide prototyping and evaluation of novel solutions to validate impact and measure ROI prior to broader implementation; evaluate new technologies and tools to enhance operational capabilities.
• Establish and enforce process governance and knowledge transfer practices for core workflow technologies (e.g., Jira); develop training to federate process expertise across the organization.
• Act as a strategic partner to senior leadership in Data, Product, and Engineering; translate complex business needs into actionable visions for process innovation and measurable business impact.

Requirements

• Deep expertise in advanced quantitative process analysis and Operations Research methodologies (e.g., simulation, optimisation/optimization, SPC, process mining).
• Proven track record of leading analytical or technical projects from conception through completion that deliver measurable business impact in efficiency, quality, or risk management.
• Exceptional strategic thinking, problem-solving, and stakeholder management skills; ability to influence senior leaders and drive change across large organizations.
• 8+ years of relevant professional experience, including 3+ years in a formal leadership or management role guiding technical or analytical teams.
• Advanced degree (MSc/PhD) in Industrial Engineering, Operations Research, Systems Engineering, or a related quantitative field.

Preferred (Nice-to-have)

• Experience in analytical, technical, or decision-science consulting roles focused on operational or systems-level transformation.
• Professional certification in process improvement methodologies (e.g., Lean Six Sigma Black Belt, CMQ/OE, TOC).
• Professional project management certification (e.g., PMP, PRINCE2, CSM).
• Experience applying methodologies in complex operational environments such as manufacturing, supply chain, or logistics.
• Experience managing hybrid teams including analytical and systems-focused specialists.
• Strong understanding of modern data stacks and how they can be leveraged to improve operational monitoring and analysis.

Compensation & Benefits

Salary Range: 135000 - 230000 USD Annually + Benefits + Bonus

The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.

We offer a comprehensive benefits plan which may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) + match, life insurance, and wellness programs. The Company does not provide benefits directly to contingent workers/contractors and interns.

How to Apply

Apply via the Bloomberg careers portal link included in the original posting. Candidates who match the role will be contacted regarding next steps.