Senior Data Management Professional - Analytics Engineer - DMO BI

Details

Bloomberg's Data organization delivers data, news, and analytics through innovative technology. The Data Management Operations (DMO) team supports data management excellence by improving discoverability, accessibility, interoperability, and analysis-readiness. The Business Intelligence team supports DMO by delivering scalable analytics, reporting, and data products to enable data-driven decisions across the organization.

Responsibilities

• 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.
• 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 (e.g., One Big Table) for BI consumers.
• Implement robust source validation, data profiling, and observability checks so stakeholders can trust the data.
• Make pragmatic tradeoffs around correctness, scope, performance, and documentation, reasoning about data semantics and grain.
• Work closely with domain experts, Product, and Engineering partners to translate complex financial data into stable analytical schemas.
• Identify analytical work worth formalizing into reusable data products and help define boundaries between foundational datasets and decision-specific products.
• Partner with Product Managers and Engineers on roadmap feasibility, tooling, architecture, and performance decisions while focusing on the data layer.

Requirements

• 4+ years of experience as a BI analyst, analytics engineer, or similar data-focused role (years used as a guide).
• Proven ability to turn messy, ambiguous data into trusted analytical assets.
• Comfortable working under ambiguity and improving things incrementally; strong collaboration skills and interest in learning data domains deeply.
• Ability to translate semi-structured producer data into stable analytical schemas (OLTP to OLAP).

Deep hands-on experience with:

• SQL-based data modeling and query optimization.
• PySpark and Pandas/Polars for data transformation and modeling.
• Analytical dataset design, storage/layout optimization, partitioning strategies, and performance/efficiency considerations.
• Designing for schema evolution, source validation, data profiling, and observability.
• Implementing CI/CD for data pipelines and automated data testing.

Nice-to-haves / desirable experience:

• Experience with complex or regulated datasets.
• Exposure to Bloomberg Terminal and Company Financials products.
• Data product or platform-style thinking, and experience partnering with domain experts or driving adoption of new systems.
• Familiarity with modern table formats and distributed query engines at scale (e.g., Iceberg/Delta; Trino/Spark) and high-concurrency BI serving patterns (OBT).

Benefits

Salary Range: 110,000 - 190,000 USD Annual + Benefits + Bonus

Bloomberg offers a comprehensive benefits plan which 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) with match, life insurance, and various wellness programs. The Company does not provide benefits directly to contingent workers/contractors and interns.