Team Leader - Private Credit Data

Team Leader - Private Credit Data

Location
London

Business Area
Data

Ref #
10044932

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 innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes.

Our Team:
We build data products that help clients navigate the evolving credit landscape, especially in areas like Loans, Private Credit, and Capital Structure. By bringing together insights from multiple sources, we deliver high-impact datasets that support decision-making in markets where transparency is limited.

We collect and connect insights from news, public filings, and direct sources to build a detailed view of Private Credit, with a focus on Direct Lending Loans. Our data brings transparency to a traditionally opaque market, covering issuance, pricing, non-accruals, defaults and supports valuation, credit modeling, and investment strategies.

Our mission is to help clients navigate complex credit markets with confidence. We continue to evolve our data, technology, and expertise to meet rising market demands and uncover new opportunities.

What's the role?

The Private Credit Team is looking for a driven Team Leader to oversee the data management, quality, and processes powering our dataset. You'll lead a team of data professionals with diverse expertise, ensuring they apply best practices and deliver accurate, client-ready data. The role requires strategic thinking, strong execution, and a focus on building a high-performing, inclusive team culture. Success will depend on close collaboration with Engineering, Product, Enterprise, and other key partners.

We'll Trust You To:

• Lead, mentor, and grow a team of data management professionals focused on delivering high-quality, time-sensitive financial data
• Drive collaboration with key partners across Product, Sales, News, and Engineering to deliver impactful, client-ready data
• Champion data governance, quality controls, and process transparency through client-centric metrics
• Guide team development in data modeling and ETL, working closely with Engineering to build scalable, multi-product data solutions
• Establish and enforce standards to ensure data meets SLAs and supports exceptional client service
• Build subject matter expertise and stay ahead of industry trends to identify gaps and innovation opportunities
• Collaborate globally to enhance workflows, ensuring consistent, efficient data quality across products and regions

• 3+ years of leadership or advanced individual contributor experience, with strong domain expertise
• Solid background in financial market data, experience with exchanges, providers, or financial institutions
• Proven experience in data management: data quality, modeling, and/or engineering
• Proficiency in data analysis tools like Python, SQL, or Tableau
• Strong communication skills to represent team needs and business priorities effectively
• Deep knowledge of fixed income credit and ability to identify market trends
• Experience working with large datasets to extract insights and inform decisions
• Ability to present clear, data-backed recommendations to guide strategy and drive outcomes
• Strategic mindset to align team goals with business priorities and deliver high-impact results
• Credibility and influence to build strong internal and external partnerships

• Strong connections or experience within the Private Credit and/or Loan industry
• Background in client-facing roles such as sales support, client service, or marketing in Private Credit
• Deep understanding of how financial data drives decisions across the business
• Proven track record delivering data-driven transformation, such as advanced data modeling, automated workflows, or data quality and governance initiatives