Bloomberg's Data Management Operations BI team seeks a Senior Data Management Professional to help shape the analytical data foundations that power reporting and insights. Based onsite in Princeton, NJ, this role centers on refining Foundational Reporting Datasets (FRDs), building scalable analytics, dashboards, and reusable data products that enable self-service analytics for a broad range of stakeholders.
In this position, you will collaborate with domain experts, engineers, and product colleagues to balance data correctness, scope, performance, and documentation while advancing the data architecture that underpins business decisions.
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, and implement CI/CD processes and automated data testing to ensure pipeline reliability
- Design storage layouts, partitioning strategies, and high-concurrency serving patterns (like One Big Table) for BI consumers
- Implement robust source validation, data profiling, and observability checks so stakeholders have absolute trust in the data
- Make pragmatic tradeoffs around correctness, scope, performance, and documentation, reasoning about data semantics and grain
- 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
- Partner with Product Managers to define roadmap feasibility, and work alongside Software Engineers to influence upstream tooling and architecture decisions
- Collaborate with engineers on performance, tooling, and modeling decisions, while remaining focused on the data layer
Requirements
- 4+ years of experience as a BI analyst, analytics engineer, or similar data-focused role
- 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)
- SQL-based data modeling
- PySpark and Pandas/Polars
- Analytical dataset design
- Performance and efficiency considerations
- Storage/layout optimization for analytical tables
- Designing for schema evolution
- Source validation and data profiling
Technologies
- SQL
- PySpark
- Pandas
- Polars
- Iceberg
- Delta Lake
- Trino
- Apache Spark
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Short-term disability benefits
- Long-term disability benefits
- 401(k) with match
- Life insurance
- Wellness programs
- Paid holidays
- Paid time off
- Merit increases
- Incentive compensation (exempt roles only)
Accommodations
Bloomberg provides reasonable adjustment/accommodation to individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process or work procedures, providing documents in an alternate format or using specialized equipment. To request an adjustment/accommodation to apply for a job, please email AMER_recruit@bloomberg.net (Americ
Equal Opportunity
Bloomberg is an equal opportunity employer and prohibits discrimination in employment. It is Bloomberg’s policy to provide equal opportunity and access for all persons, and the Company is committed to attracting, retaining, developing, and promoting the most qualified individuals without regard to 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, self-identif
