Senior Data Management Professional - Data Engineering - Commodities Data

Details

Bloomberg's Data organization delivers data, news, and analytics through innovative technology. The Commodities Data Team is responsible for onboarding, modelling, and maintaining data across Power and Gas, Oil, Carbon, Agriculture, and Metals.

The team is seeking a highly experienced data engineering professional to help lead the next generation of its data platform. The role combines data engineering with ownership of data quality, building quality directly into pipelines, systems, and architecture.

Responsibilities

• Build and maintain scalable, resilient, and observable data pipelines supporting critical commodities datasets.
• Modernize legacy workflows to reduce technical debt and improve maintainability and performance.
• Perform data profiling, deep data analysis, and root cause analysis to support data-driven decision-making.
• Build and deploy automated data quality controls, anomaly detection, and proactive monitoring.
• Apply artificial intelligence and machine learning techniques, including natural language processing, entity extraction, and anomaly detection, to improve data ingestion and enrichment.
• Identify opportunities to use generative AI and automation to reduce manual workflows and accelerate data onboarding.
• Develop validation frameworks for agentic artifacts to ensure quality, reliability, and appropriate controls.
• Own and drive large-scale data migrations and system redesigns.
• Establish best practices for data architecture, pipeline design, and workflow orchestration.
• Understand how clients consume data across Bloomberg products and translate client needs into measurable data quality and product improvements.
• Partner with Engineering on platform evolution, scalability, and system design.
• Act as a technical leader and mentor, raising standards for code quality, design thinking, and execution.
• Apply project management expertise to keep technical projects aligned with requirements and on track.

Requirements

• Bachelor's degree or above in Statistics, Computer Science, Quantitative Finance, another 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 Python experience in development or production environments.
• Experience working with SQL and/or NoSQL databases.
• Proven experience 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 AI or machine learning techniques in data workflows, such as classification, NLP, anomaly detection, or LLM-assisted workflows.
• Strong data quality management experience, 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 improve performance and scalability.
• Familiarity with databases, schemas, data modelling, and structured and unstructured formats including PDF, HTML, XBRL, JSON, and CSV.
• Strong communication and interpersonal skills, including the ability to influence technical direction, mentor team members, communicate complex concepts, and collaborate across distributed teams.

Preferred Qualifications

• Advanced degree in a relevant subject and/or Certified Data Management Professional certification, or progress toward certification.
• Experience with Bloomberg products, Bloomberg Terminal, or Bloomberg Data Workflows.
• Experience with commodities markets and products.
• Experience productionizing AI or machine learning models within data platforms.
• Experience driving efficiency gains through automation and intelligent systems.
• Strong understanding of data governance, lineage, and metadata management at scale.
• Hands-on project management experience with familiarity with JIRA and QlikSense.

Benefits

The compensation package 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.

Salary range: $110,000–$190,000 USD annually, plus benefits and bonus. Actual compensation may vary based on geographic location, work experience, market conditions, education, training, and skill level.