Senior Data Management Professional - Data Engineering - Physical Assets

at  Bloomberg

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.
The Physical Assets Data Team maintains databases for physical assets such as renewable and conventional power plants, facilities, storage projects globally. The team is currently working on a new future-proof data model and workflow that can facilitate and accelerate coverage expansion for integrated use in downstream analysis across our customer groups (including governments, portfolio managers, corporations, equity analysts etc.).

As a Data Engineer on the Physical Assets team, you’re required to understand the data requirements, specify the modeling needs of datasets and use existing techstack solutions for efficient data ingestion workflows and data pipelining. You will implement technical solutions using programming, machine learning, AI, and human-in-the-loop approaches to make sure our data is fit-for-purpose for our clients. You will work closely with our Engineering partners, our Data Product Manager as well as Product teams, so you need to be able to coordinate with multi-disciplinary and regional teams and have experience in project management and stakeholder engagement. You will need to be comfortable working with large, varied, sophisticated and often unstructured data sets and you will need to demonstrate strong experience in data engineering.

We trust you to:

• Build database schema and configure ETL software to onboard new data sets
• Analyze internal processes to find opportunities for improvement, as well as devise and implement innovative solutions
• Build quality data workflows to verify and validate third party data
• Maintain workflow configurations for critical functions such as acquisition, worklist management, and quality control
• Contribute to the creation of best practices and guidelines for governance
• Partner with Engineering and Product to propose, develop and implement market leading solutions for our clients
• Understand customer needs and markets to ensure our data sets are fit-for-purpose and seamlessly integrate with other data products when developing -data product strategies
• Stay updated on market, industry and dataset developments related to your area of support
• Make well-informed decisions in a fast-paced, ever-changing environment
• Report on results of on-going operations and projects, as required