Description & RequirementsThe Role:The Alternative Investment Funds Data Engineers are a dynamic group of individuals who tackle the most challenging aspects of our data product including data pipelining, process engineering and driving innovation. Our Data Engineers possess a unique combination of technical skills, domain expertise and eye for business, as well as good communication and interpersonal skills. As such, we are looking for a highly motivated individual with a passion for data and the technology that surrounds it.
As a Data Engineer you will apply your problem-solving skills to handle the data pipelines, automation processes and human-in-the-loop workflows that feed our Private Funds and Hedge Funds Data Products. In addition to the data pipelining work, you will analyze our data from an operational as well as product standpoint. This might be by building the associated ETLs or by designing prototype applications with our product teams. You will be expected to lead projects, collaborate with Engineering and Product, and own the end-to-end delivery of your project.
We'll trust you to:- Build and enhance data pipelines and processes that powers Bloomberg's Private Funds and Hedge Funds Databases, ensuring high data quality, consistency, and reliability.
- Identify opportunities for automation and implement scalable ETL solutions, including human-in-the-loop data workflows and custom tooling, to support the rapid growth and evolving needs of the product.
- Leverage your technical expertise to streamline and standardize pipelining practices across the team and broader department, promoting efficiency and knowledge sharing.
- Work closely with Engineering, Product, and Sales teams to drive end-to-end development, gather requirements, and deliver impactful data solutions that align with business goals.
- Take full ownership of existing data pipelines and services in production, proactively ensuring their stability, reliability, and continuous improvement.
- Help shape and elevate the team's operational standards by contributing to best practices in technical development, cross-team collaboration, and ongoing service reliability.
You'll need to have:- A BA/BS degree or higher in Computer Science, Statistics, or relevant data technology field, or equivalent professional work experience
- 4+ years of Python programming and scripting in a production environment
- 4+ years of experience working with NoSQL databases
- Understanding and experience in large-scale distributed systems
- Strong problem solving skills, particularly to modify and improve processes and workflows
- Excellent written and verbal communication skills, especially when explaining technical processes and solutions to business partners and management
- High attention to detail and degree of shown decision-making and problem-solving skills
- Ability to work independently as well as in a distributed team environment
- Ability to influence others and lead change
- Experience in conducting technical training and mentoring others
We'd love to see:- Financial Markets experience including an understanding of the private markets industry
- Understanding of Machine Learning, applied statistics and data analytics
- Agile/Scrum Project Management experience
If this sounds like you:Apply! If you think we're a good match. We'll get in touch to let you know the next steps!
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.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that 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.
