Data Analyst

Skills

About the Role

You will translate questions into insight and partner with cross functional teams to turn ambiguous business and operational questions into clear actionable analyses. You will write clean SQL against PostgreSQL Trino and Apache Iceberg to power core metrics and dashboards. You will surface metrics through Metabase and explore data with Python in a Jupyter notebook to understand trends and trading behaviors. You will help standardize core data entities and support self serve reporting.

Requirements

• Strong SQL fundamentals with joins, CTEs, window functions and clear query structure across diverse database environments.
• Analytics Engineering Familiarity with building analytical data models or metrics tables using dbt or similar workflows.
• Deep Analytical Intuition and ability to ask the right questions, synthesize clear conclusions and avoid rabbit holes.
• Python and Notebook Proficiency with the ability to use Python (Pandas NumPy) and Jupyter Notebooks for deeper analysis.
• Clear Communicator and Collaborator capable of sharing insights with technical and non technical partners and acting as a bridge between data infrastructure and business operations.
• Domain Agility with a quick ability to learn the intricacies of a broker dealer environment including clearing infrastructure and financial accounting standards.

Responsibilities

• Translate questions into insight and partner with cross functional teams to turn ambiguous business and operational questions into clear, useful analytical outputs, assimilating subject matter expertise across brokerage operations, ledger systems, and compliance.
• Build and own analytics data models. Write clean, maintainable SQL against PostgreSQL, Trino, and Apache Iceberg to power core financial metrics, dashboards, and analytical workflows.
• Build and iterate on metrics and tables using dbt, surfacing them through dashboards in Metabase to help teams understand transaction volumes, revenue streams, and system performance over time.
• Explore data deeply to answer open ended questions using SQL as the primary tool, with Python in a notebook environment like Jupyter when helpful, to investigate trends, anomalies, complex profit and loss calculations, and trading behaviors.
• Help operationalize data by standardizing core business entities and transitioning ad hoc analytical requests into intuitive self serve environments.
• Assist with reporting capabilities and streamline report automation, including servicing requests, cataloguing recurring reports, and driving conversations around standardization and productization of data reports.

Benefits

• Stock Options
• Health Benefits
• New Hire Home Office Setup: One-time USD 500
• Monthly Stipend: USD 150 per month via a Brex Card