Team Leader - Equity Corporate Actions - M&A, IPO and Private Deals Data

Location: London

Business Area: Data

Ref #: 10051480

Description & Requirements

Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem‑solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products and processes.

Our Team:

Our Equity Corporate Actions Data team underpins Bloomberg’s Terminal and enterprise services by sourcing, validating, and publishing accurate equity reference and corporate‑actions information—from distributions, to mergers & acquisitions, stock splits, spin‑offs, and beyond—to hundreds of thousands of users worldwide. Within this group, this role will focus on leading coverage of deal‑related datasets, including mergers & acquisitions, IPOs, and private deals.

What’s the Role?

We’re looking for a strong people leader to join our group in London where you will lead and develop a team of Corporate Actions analysts covering the EMEA region. Your role is key in ensuring consistency of standards for the delivery of accurate and timely financial data to our worldwide clients, while continually seeking new ways to operate more efficiently. Working with your team, you will be expected to drive the delivery of our day‑to‑day product offerings, while leveraging technology to automate and evolve our data product for the future. You will have the opportunity for extensive collaboration with global colleagues across all business units, including Product, Engineering, and News.

We’ll trust you to:

• Lead & mentor a team of Corporate Actions analysts, delivering day‑to‑day on what our clients rely on, while developing the new skill‑sets needed to evolve the group
• Coach analysts to connect daily tasks to long‑term data‑product strategy, fostering ‘big-picture’ thinking
• Instill a high‑performance, feedback‑rich culture that recognizes excellence and drives continuous learning
• Champion end‑to‑end data stewardship by embedding robust governance frameworks that safeguard consistency and integrity across every data element
• Orchestrate automation at scale—combine AI/ML extraction with structured data‑management techniques, via a combination of proprietary and industry standard toolkit, to streamline validation, enrichment, and reconciliation to maximize data product value
• Ensure fit‑for‑purpose quality by tracking accuracy, timeliness, completeness, coverage, and continuity KPIs, and rapidly correcting anomalies surfaced via business‑intelligence analytics
• Evolve the data product in partnership with Product and Engineering—advance data‑model architecture, integrate new sources, and pilot novel LLM‑powered solutions to deliver measurable client value
• Deliver client‑first service by upholding strict SLAs, resolving incidents fast, and translating client feedback into prioritized backlog items that continually raise the bar on user satisfaction

You’ll need to have:

• Led a high‑performing team of data analysts or subject‑matter experts for 3+ years, setting clear targets and coaching for continuous improvement
• Demonstrated deep hands‑on expertise in data quality, data modelling, and data engineering, plus hands‑on command of modern processing paradigms, tools, and architectures
• Built and operationalized production‑grade data pipelines that ingest, normalize, validate, publish, and continuously improve large‑scale financial datasets
• Provided advanced SQL and Python (or similar languages) guidance to teammates developing automation pipelines and data validation rules
• Acquired in‑depth knowledge of the Equity Corporate Actions domain, particularly datasets related to mergers & acquisitions, IPOs, and private deals, and its downstream use‑cases
• Established influential relationships with internal and external stakeholders and communicated complex data‑management concepts clearly to both technical and non‑technical audiences
• Solved problems creatively and flexibly, leveraging strong analytical skills to turn data insights into actionable improvements

We’d love to see:

• Advanced degree in a data‑related discipline — or a recognized credential such as the DAMA Certified Data Management Professional (CDMP)
• Contribution to corporate actions working groups or standards bodies, demonstrating thought‑leadership in data‑management best practices.