Senior Data Management Professional - Data Product Owner - Environmental Regulations

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Senior Data Management Professional - Data Product Owner - Environmental Regulations

Location

London

Business Area

Data

Ref #

Description & Requirements

Sustainable Finance data is increasingly crucial for our clients providing deeper intelligence than conventional financial analysis alone. Climate change, regulatory pressures, the importance of human capital, and diversity are just a few critical factors global investors consider to best identify emerging risks and opportunities. At Bloomberg, Sustainable Finance data is displayed alongside fundamental data, backed by news for context, and used to power a growing suite of Sustainable Finance data products.

As a team, we are responsible for reporting and improving Sustainable Finance-related content for the Bloomberg Terminal and Enterprise products, including company-reported and normalized metrics, key analytical ratios, industry-specific metrics, and proprietary scores. Joining the Data department means that you are a part of one of the world's leading sources of data, providing accurate, immediate insights for financial market professionals. You will enhance your product knowledge, learn about our clients and their needs, and build relationships throughout the company, all while helping our clients integrate sustainable finance risk and opportunity analysis into their workflows.

The Role:

As a Data Product Owner in the Sustainable Finance Regulatory Data team, you will own the data management strategy, operating model and roadmap for Bloomberg's environmental regulatory data products, including EU Taxonomy, SFDR, CSRD, and evolving regulatory product needs. Working closely with Product, Engineering, Enterprise Product and Sales, you will translate evolving regulatory requirements into scalable, high quality fit-for-purpose data products through robust data models, quality frameworks and operational processes.

You will define the standard for excellence for these products from content design and quality management through to transparency, auditability and operational excellence.

You will continuously evolve these products by translating regulatory change into practical data requirements, scalable operating models and workflow improvements, while finding opportunities to simplify and automate processes, leverage AI and improve how regulatory data is collected, managed and delivered.

We'll trust you to:

• Own the data management strategy, roadmap and operating model for a portfolio of environmental regulatory data products including EU Taxonomy, SFDR and CSRD.
• Continuously evolve the content model, quality standards and fit-for-purpose criteria for each product.
• Partner closely with Engineering and Product to evolve data models, metadata structures, workflow tooling and architecture that enable scalable, reusable and high quality data products.
• Design and continuously improve quality management frameworks, governance processes and operational controls that ensure trusted, auditable and scalable data products.
• Own measurable data product health metrics, including quality, coverage, timeliness, lineage and transparency.
• Translate evolving regulatory requirements into clear data requirements and product enhancements.
• Define data content and annotations that support both human and AI-assisted data collection.
• Find opportunities to modularize, automate, and orchestrate workflows, moving from one-off projects to a reusable operational layer.
• Apply strong product thinking and technical expertise to define and drive the strategic evolution of products and processes under your remit, ensuring robust quality metrics are created and used to iterate on workflows and performance.
• Build deep understanding of client workflows, market developments and regulatory change to recommend data driven enhancements, prioritise investment and inform the evolution of Bloomberg's environmental regulatory data products.
• Own and continuously evolve an iterative roadmap using a data-driven approach to prioritization.

You'll need to have:

• 4+ years of demonstrated expertise in data management, including data quality, governance, metadata management, data modelling and lifecycle management.
• Deep knowledge of environmental regulatory reporting frameworks including SFDR, CSRD, EU Taxonomy, PAB, CTB and related disclosure requirements.
• Proven experience designing, implementing and continuously improving fit-for-purpose quality management frameworks, measurable data quality controls and data product health indicators.
• Experience in translating regulatory, technical and data quality concepts into clear requirements, documentation and stakeholder-ready recommendations.
• Experience defining data content and annotation standards to support both human and AI-assisted data collection.
• Experience defining data models, content standards or metadata structures that support scalable, reusable data products.
• Experience owning the end-to-end lifecycle of a data product, from requirements and design through delivery, measurement and continuous improvement.
• Strong technical proficiency, including Python, SQL and modern AI-assisted development tools, with the ability to partner effectively with Engineering on data architecture, modelling and implementation decisions.
• Experience applying generative AI and AI-assisted development tools to improve data management workflows, quality assurance, content management and operational efficiency.
• Excellent stakeholder management and communication skills with the ability to influence Product, Engineering, Enterprise Product and Sales.
• Excellent problem-solving and analytical thinking skills, with strong attention to detail.

Please note: years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

We'd love to see:

• Strong knowledge and understanding of the Sustainable Finance market and sustainable finance data client needs.
• Experience working with a range of regulatory disclosure frameworks and standards, including but not limited to TCFD, ISSB, GRI.
• Experience implementing AI-enabled data collection or quality workflows.
• Experience in using Bloomberg Data, Bloomberg Terminal, and/or enterprise financial data products.
• Past project experience using Agile/Scrum methodologies to manage complex data lifecycles.
• DAMA, CDMP or DCAM certifications

If this sound like you:

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

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