Jobangebot connecticum Job-1757618
Bloomberg L.P.
Jobdatum: 22. August 2024
Info zum Arbeitgeber
Bloomberg L.P.
Financial News, Data and Analytics
Firmensprache
Deutsch, Englisch
Mitarbeiter
10.001 - 50.000
Kontakt
Bloomberg Recruitment Team
City Gate House
39-45 Finsbury Square
London
EC2A 1PQ
+44 20 7330 7500
Online applications only
Homepage
www.bloomberg.com
Karriere-Website
www.bloomberg.com/careers
Senior Data Management Professional - Data Engineering - Physical Assets 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.). What's the role?
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:
You’ll need to have:
*Please note we use years of experience as a guide but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.
We’d love to see:
Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are! Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg provides reasonable adjustment/accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job or to perform your job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you would prefer to discuss this confidentially, please email AMER_recruit@bloomberg.net (Americas), EMEA_recruit@bloomberg.net (Europe, the Middle East and Africa), or APAC_recruit@bloomberg.net (Asia-Pacific), based on the region you are submitting an application for. Alternatively, you can get support from our disability partner EmployAbility, please contact +44 7852 764 684 or info@employ-ability.org.uk |
Senior Data Management Professional - Data Engineering - Physical Assets