Senior Data Management Professional – Analytics Engineer

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
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

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
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)
Deep hands-on experience with:
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

We would love to see:
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)