Senior Data Management Professional - Analytics Engineer - DMO BI

Details

Bloomberg's Data Management Operations (DMO) supports data management excellence by aligning industry best practices with Bloomberg's expertise in financial market data. The Business Intelligence team helps data teams and stakeholders make informed, data-driven decisions through scalable analytics, reporting, and data products.

This hands-on role focuses 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 with domain experts, Product, and Engineering partners to translate complex financial data into stable analytical schemas that support scalable reporting and reuse.

Responsibilities

• Build, maintain, and evolve Foundational Reporting Datasets (FRDs) for reporting and analysis.
• Write and optimize SQL queries to clean, shape, and model noisy, real-world data into performant, reusable datasets.
• Write modular, version-controlled SQL and PySpark.
• Implement CI/CD processes and automated data testing to ensure pipeline reliability.
• Design storage layouts, partitioning strategies, and high-concurrency serving patterns such as One Big Table (OBT) for BI consumers.
• Implement source validation, data profiling, and observability checks.
• Make pragmatic tradeoffs involving correctness, scope, performance, and documentation while reasoning about data semantics and grain.
• Work with domain experts and stakeholders to understand how data is produced, interpreted, and used.
• Build domain intuition and represent data accurately in cross-functional discussions.
• Identify analytical work that should be formalized into reusable data products.
• Help define boundaries between foundational datasets and decision-specific, reusable data products.
• Partner with Product Managers to define roadmap feasibility.
• Work with Software Engineers on performance, tooling, modeling, upstream architecture, and data-layer decisions.

Requirements

• 4+ years of experience as a BI analyst, analytics engineer, or in a similar data-focused role.
• Proven ability to turn messy, ambiguous data into trusted analytical assets.
• Comfort working under ambiguity and improving systems incrementally.
• Strong collaboration skills and interest in learning a data domain deeply.
• Ability to translate semi-structured producer data into stable analytical schemas, including OLTP-to-OLAP transformations.
• Deep hands-on experience with SQL-based data modeling.
• Deep hands-on experience with PySpark and Pandas/Polars.
• Experience designing analytical datasets.
• Understanding of performance and efficiency considerations.
• Experience optimizing storage and layouts for analytical tables.
• Experience designing for schema evolution, source validation, and data profiling.

Preferred Qualifications

• Experience working with complex or regulated datasets.
• Experience using Bloomberg Terminal and Company Financials products.
• Exposure to data product or platform-style thinking.
• Experience partnering closely with domain experts or subject-matter experts.
• Experience driving adoption of new systems.
• Interest in data governance, ownership, and reuse patterns.
• Familiarity with modern table formats and distributed query engines at scale, such as Iceberg, Delta, Trino, Spark, or equivalents.
• Exposure to high-concurrency BI serving patterns such as OBT.

Benefits

Benefits and total rewards may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.