• 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.
• Partner with engineers on performance, tooling, and modeling decisions, while remaining focused on the data layer itself

• 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

• 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 SMEs
• 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 (e.g., Iceberg/Delta; Trino/Spark or equivalents)
• Exposure to high-concurrency BI serving patterns (OBT)

Does this sound like you?

Apply if you think we're a good match. We'll get in touch to let you know what the next steps are!