Senior Data Management Professional - Company Financials, Analytics Engineer
UK Visa Sponsorship Analytics
Analytics are greyed out due to low classification confidence (51.0%).
Occupation Type
Actuaries, economists and statisticians
Occupation Code Skill LevelHigher Skilled
Sponsorship Salary Threshold
£55,100
(£28.26 per hour)
Occupation rate applies
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Description
Location
London
Business Area
Data
Ref #
10049292
Description & Requirements
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 workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Our Team
The Company Financials (CoFi) Data team provides clients with fast, accurate, and trusted financial data that powers analysis across markets and industries. Our datasets support reporting, modeling, and insight generation for internal stakeholders and external clients.
We combine financial domain expertise, data modeling, analytics engineering, and technical rigor to create high-quality, performant analytical datasets that support a wide range of reporting and decision-making needs.
What's the role?
As a Senior Data Management Professional within the Business Intelligence team, you will play a key role in shaping and evolving the analytical data foundations that power our reporting platform.
This is a hands-on, data-focused role centered on building, modeling, and optimizing analytical datasets. You will own and evolve Foundational Reporting Datasets (FRDs), ensuring they are accurate, performant, reusable, and aligned with domain realities. You will work closely with domain experts, Product, and Engineering partners to translate complex, real-world financial data into stable analytical schemas that support scalable reporting and reuse.
Your work will directly influence how data is trusted, modeled, and reused across teams, balancing immediate analytical needs with long-term scalability and governance.
We'll Trust You To
London
Business Area
Data
Ref #
10049292
Description & Requirements
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 workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Our Team
The Company Financials (CoFi) Data team provides clients with fast, accurate, and trusted financial data that powers analysis across markets and industries. Our datasets support reporting, modeling, and insight generation for internal stakeholders and external clients.
We combine financial domain expertise, data modeling, analytics engineering, and technical rigor to create high-quality, performant analytical datasets that support a wide range of reporting and decision-making needs.
What's the role?
As a Senior Data Management Professional within the Business Intelligence team, you will play a key role in shaping and evolving the analytical data foundations that power our reporting platform.
This is a hands-on, data-focused role centered on building, modeling, and optimizing analytical datasets. You will own and evolve Foundational Reporting Datasets (FRDs), ensuring they are accurate, performant, reusable, and aligned with domain realities. You will work closely with domain experts, Product, and Engineering partners to translate complex, real-world financial data into stable analytical schemas that support scalable reporting and reuse.
Your work will directly influence how data is trusted, modeled, and reused across teams, balancing immediate analytical needs with long-term scalability and governance.
We'll Trust You To
- Build, maintain, and evolve Foundational Reporting Datasets (FRDs) that serve as the analytical backbone for reporting and analysis
- Write and optimize SQL queries to clean, shape, and model noisy, real-world data into performant, reusable datasets
- Make pragmatic tradeoffs around correctness, scope, performance, and documentation, reasoning about data semantics and grain
- Continuously improve data quality, clarity, and query efficiency
- Work closely with domain experts and stakeholders to understand how the data is produced, interpreted, and used
- Actively build domain intuition over time — learning why the data behaves the way it does, not just how it’s structured
- Represent the data accurately and confidently in cross-functional discussions
- Identify analytical work that is worth formalizing into reusable data products
- Help define clear boundaries between foundational datasets and decision-specific, reusable data products
- Collaborate with a Product Manager who owns roadmap and prioritization, providing deep input into feasibility and tradeoffs
- Partner with engineers on performance, tooling, and modeling decisions, while remaining focused on the data layer itself
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.
- 4+ years of experience as a BI analyst, analytics engineer, or similar data-focused role
- Deep hands-on experience with, SQL-based data modeling, PySpark and Pandas/Polars, analytical dataset design, performance and efficiency considerations as well as storage/layout optimization for analytical tables
- Experience designing for schema evolution and the ability to source validation and data profiling
- Proven ability to turn messy, ambiguous data into trusted analytical assets
- Comfort working under ambiguity and improving things incrementally
- Strong collaboration skills and interest in learning a data domain deeply
- Ability to translate semi-structured producer data into stable analytical schemas (OLTP to OLAP)
- Experience working with complex or regulated datasets
- Experience using Bloomberg Terminal and Company Financials products
- Exposure to data product or platform-style thinking