Team Leader - Equity Corporate Actions - M&A, IPO and Private Deals Data
Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Communication @ 7
Data Engineering @ 6
Data Pipelines @ 4
LLM
Leadership @ 6
Machine Learning
Python @ 6
SQL @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg’s Data organization delivers data, news, and analytics through innovative technology. The Equity Corporate Actions Data team sources, validates, and publishes equity reference and corporate-actions information, including distributions, mergers and acquisitions, stock splits, spin-offs, IPOs, and private deals, for Bloomberg Terminal and enterprise services.
This role leads and develops a team of Corporate Actions analysts covering the Americas region. The position is responsible for maintaining consistent standards for accurate and timely financial data delivery, improving operational efficiency through technology, and collaborating with Product, Engineering, News, and global business-unit colleagues.
Responsibilities
- Lead and mentor a team of Corporate Actions analysts delivering day-to-day data products and developing new capabilities.
- Coach analysts to connect daily tasks with long-term data-product strategy.
- Build a high-performance, feedback-rich culture that supports continuous learning.
- Establish end-to-end data stewardship and governance frameworks to maintain data consistency and integrity.
- Orchestrate automation at scale by combining AI/ML extraction with structured data-management techniques and proprietary and industry-standard tools.
- Streamline data validation, enrichment, and reconciliation processes.
- Track accuracy, timeliness, completeness, coverage, and continuity KPIs, and correct anomalies identified through business-intelligence analytics.
- Evolve data products with Product and Engineering by advancing data-model architecture, integrating new sources, and piloting LLM-powered solutions.
- Uphold strict SLAs, resolve incidents quickly, and convert client feedback into prioritized backlog items.
Requirements
- Bachelor’s degree with at least 4 years of relevant experience, or a Master’s degree with at least 3 years of relevant experience.
- At least 3 years of experience leading a high-performing team of data analysts or subject-matter experts, including setting targets and coaching for continuous improvement.
- Deep hands-on expertise in data quality, data modelling, and data engineering.
- Hands-on knowledge of modern data-processing paradigms, tools, and architectures.
- Experience building and operationalizing production-grade data pipelines that ingest, normalize, validate, publish, and continuously improve large-scale financial datasets.
- Advanced SQL and Python, or similar programming languages, with the ability to guide teammates developing automation pipelines and data-validation rules.
- In-depth knowledge of Equity Corporate Actions, particularly mergers and acquisitions, IPOs, and private deals, and their downstream use cases.
- Strong stakeholder-management and communication skills, including the ability to explain complex data-management concepts to technical and non-technical audiences.
- Strong analytical, creative, and flexible problem-solving skills.
Preferred Qualifications
- Advanced degree in a data-related discipline or a recognized credential such as the DAMA Certified Data Management Professional (CDMP).
- Contributions to corporate-actions working groups or standards bodies, demonstrating thought leadership in data-management best practices.
Benefits
Benefits and total rewards may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.