Senior Data Management Professional - Automation Engineer - Classifications
Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 6
Tableau @ 4
Machine Learning @ 4
Communication @ 4
BI @ 4
NLP @ 4
Agile @ 4
AI @ 4
Data Visualization @ 4
Data Pipelines @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
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 innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes.
Team
The Classifications team builds and maintains the taxonomies that group companies and securities by business activities and risk profiles. These classifications form the foundation for peer group analysis, benchmarking, and market trend evaluation. When clients compare investment opportunities, evaluate sector exposures, or analyze historical performance, classification data provides the consistent framework that makes these insights possible.
We enable clients to:
- Assess how global, regional, or local industry trends affect portfolios
- Compare and report on sector exposures versus peers and benchmarks
- Identify investment opportunities across developed and emerging markets
- Analyze sector and industry contributions to portfolio performance
- Build consistently defined, sector-based investment and rotation strategies
Role summary
As a Classifications Automation Engineer, you will be responsible for streamlining and scaling the delivery of classification data across asset types by designing and implementing automated workflows. You will partner with stakeholders to identify inefficiencies, apply modern technologies (including AI/ML where appropriate), and build solutions that improve data accuracy, consistency, and timeliness.
You will play a key role in transforming manual or semi-manual processes into robust, automated pipelines while developing business intelligence to monitor performance and outcomes.
Responsibilities
- Analyze and optimize existing workflows, identifying opportunities for automation and scalability
- Design, build, and maintain automated data pipelines and tools to improve efficiency and accuracy
- Evaluate and apply AI/ML/NLP techniques to enhance classification processes and decision-making
- Partner with Data, Engineering, Product, and Business teams to deliver scalable solutions
- Develop metrics and monitoring to ensure data quality, timeliness, and operational performance
- Understand financial datasets and client use cases to inform automation priorities
Requirements
- Bachelor’s degree with at least 4 years of relevant experience, or a Master’s degree with at least 3 years of relevant experience
- 4+ years of Python programming and scripting in a production environment
- Experience building or maintaining automated workflows, pipelines, or data systems
- Knowledge of Artificial Intelligence (AI), Natural Language Processing (NLP), or Machine Learning (ML) concepts
- Strong analytical thinking and problem-solving skills with attention to detail
- Effective communication and collaboration skills across technical and non-technical teams
- Adaptability and a proactive approach to driving change and improvement
- Legal authorization to work full-time in the United States without current or future visa sponsorship
Preferred
- Experience with Agile development methodologies (e.g., Scrum)
- Familiarity with the Bloomberg Terminal
- Knowledge of financial markets and instruments
- Experience with data visualization or BI tools such as Tableau or Qlik Sense
Compensation & Benefits
Salary Range: 110,000 - 190,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
Bloomberg offers comprehensive benefits 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. The Company does not provide benefits directly to contingent workers/contractors and interns.