Senior Data Management Professional - Data Engineer - Capital Structure

Senior Data Management Professional - Data Engineer - Capital Structure

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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.

Location
London

Business Area
Data

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Our teams operate at the forefront of Fixed Income innovation, building and maintaining foundational data products that power credit and risk workflows across institutional finance. In Capital Structure, our products are core to credit risk analysis, enabling clients to assess the complete financial structure of a corporate group, including maturity distribution, payment waterfall, guarantees, and resource mapping. Especially for high‑yield and leveraged segments, accurate capital structure data is increasingly indispensable for integrating financials, valuations, and credit assessments.

The growing focus on this area is amplified by our recent expansion into Loans indices, which further elevate data expectations.

We are looking for a Data Engineer with a strong foundation in data quality to help us acquire, process, and monitor the datasets that power our products. In this role, you will design and maintain data acquisition pipelines, support data extraction efforts, and take ownership of several data quality initiatives, including establishing new measurement frameworks, anomaly detection, and monitoring solutions. You will implement solutions using traditional programming, machine learning and AI, and human‑in‑the‑loop approaches to ensure our data is fit‑for‑purpose for our clients.

You will work closely with our Engineering partners, our Data Product Owner as well as Product teams, and you will need to coordinate with multi‑disciplinary and regional teams and have experience in project management and stakeholder engagement. You should be comfortable working with large datasets and have strong experience in data engineering.

• Build, optimize, and maintain data pipelines for acquisition, ingestion, and transformation of diverse datasets, with a focus on ensuring high quality outputs
• Lead and own data quality initiatives such as measurement, anomaly detection, monitoring, and reporting
• Design and implement automated data quality checks, metrics, and alerts within ETL/ELT workflows
• Support data extraction and integration efforts, ensuring reliability and scalability
• Collaborate closely with Product and Engineering to define priorities, align on requirements, and deliver end‑to‑end data solutions
• Identify opportunities for process improvements and infrastructure enhancements to elevate data quality and pipeline efficiency
• Apply statistical methods and data profiling to evaluate and continuously improve data quality
• Engage stakeholders across regions and disciplines, providing technical guidance and building awareness of data quality best practices
• Stay current on data engineering trends, tools, and industry standards to strengthen our technical capabilities

• 4+ years of professional experience in data engineering or related fields, with proven ability to design, build, and maintain data pipelines at scale
• Hands‑on expertise in developing and implementing data quality initiatives such as measurements and metrics, anomaly detection, monitoring, and reporting
• Strong knowledge of ETL/ELT processes, workflow orchestration, and modern data architecture concepts
• Proficiency in data profiling and analysis, tools such as Python and SQL
• Experience integrating data from diverse sources and ensuring reliability, scalability, and accuracy across large datasets
• Strong communication and stakeholder management skills, with the ability to lead…