Senior Data Management Professional - Data Engineering - Commodities Data

Details

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.

Responsibilities

In the Commodities Data Team, we’re responsible for onboarding, modelling and maintaining data that are fit for purpose for our clients. More than 320,000 business leaders rely on the real time financial information available on the Bloomberg Professional Service. Our products run on intelligence and insight provided by the Commodities Team. Our team of analysts provide valuable data and insights to key decision makers within the commodity markets.

We are responsible for the data management of datasets across Power and Gas, Oil, Carbon, Agriculture and Metals. The team provides relevant, timely and accurate data to empower customers to drive their analysis of commodity markets, both pricing and fundamentals.

The role is for a highly experienced Senior Data Management Professional to help lead the next generation of our data platform. This role requires a strong data engineering foundation combined with deep ownership of data quality, where quality is built directly into pipelines, systems and architecture rather than managed as a separate function. This role is designed for a top-tier individual contributor who thrives in complex environments and consistently delivers high-impact, scalable solutions.

You will be responsible for:

• Designing and evolving data systems that power Tier 1 datasets, improving reliability, reducing technical debt and modernizing legacy workflows
• Building advanced ETL pipelines
• Implementing intelligent automation
• Developing robust data quality controls and monitoring frameworks to ensure data accuracy, completeness and timeliness
• Defining and executing the data quality vision for datasets, including evolving fit-for-purpose quality metrics
• Understanding how clients consume data across Bloomberg products and aligning data with both client needs and Bloomberg’s commercial strategy
• Influencing data governance practices and lifecycle management across teams to ensure long-term data integrity and scalability
• Collaborating with Product, Engineering and domain experts to define and execute strategic data initiatives
• Acting as a technical leader within the team by owning end-to-end solutions, influencing architecture decisions and mentoring others
• Leveraging modern technologies including AI and machine learning to enhance data workflows and extract additional value from datasets

Requirements

• Bachelor’s degree or above in Statistics, Computer Science, Quantitative Finance or other STEM related field or degree-equivalent qualifications
• 4+ years of experience architecting, designing and implementing scalable data solutions and ETL pipelines, including monitoring, remediation and data management workflows across diverse data sources
• 4+ years of hands-on experience working with Python in development/production environment and working with databases either SQL/NoSQL
• Proven track record of owning and delivering complex, high-impact data initiatives end-to-end
• Strong experience with distributed data systems, workflow orchestration and scalable architecture design
• Hands-on experience applying machine learning or AI techniques in data workflows such as classification, NLP, anomaly detection or LLM-assisted workflows
• Strong experience in data quality management, including defining metrics, performing root cause analysis and driving measurable improvements in data reliability
• Experience building observable systems with monitoring, alerting and data reliability frameworks
• Ability to analyze and refactor legacy systems and drive measurable improvements in performance and scalability
• Familiarity with various databases, schemas, modeling, as well as structured and unstructured formats (PDF, HTML, XBRL, JSON, CSV etc.)
• Strong communication and interpersonal skills, with the proven ability to influence technical direction, mentor team members, clearly communicate complex concepts and methodologies, and effectively collaborate across diverse and distributed teams

Benefits

• Comprehensive and generous benefits plans, which may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs (among others)
• The Company does not provide benefits directly to contingent workers/contractors and interns.