Staff Analytics Engineer - Alpaca

About Alpaca

Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more. We are a licensed financial services company serving hundreds of financial institutions across 40 countries with our institutional-grade APIs, supporting over 10 million brokerage accounts. Our diverse global team is dedicated to opening financial services to everyone, with a strong commitment to open-source contributions and fostering a vibrant community.

About the Role

We are seeking an Analytics Engineer to own and execute the vision for our data transformation layer. You will be at the heart of our data platform, processing hundreds of millions of events daily from various sources. You will work closely with Data Engineers, Data Scientists, and Business Users, utilizing dbt and Trino on our GCP-based, open-source data infrastructure to build robust, scalable data models critical for stakeholders across finance, operations, and executive teams.

What You'll Do

• Own the Transformation Layer: Design, build, and maintain scalable data models using dbt and SQL to support diverse business needs.
• Set Technical Standards: Establish and enforce best practices for data modeling, development, testing, and monitoring to ensure data quality, integrity, and discoverability.
• Enable Stakeholders: Collaborate with finance, operations, customer success, and marketing teams to understand requirements and deliver reliable data products.
• Integrate and Deliver: Create repeatable patterns for integrating data models with BI tools and reverse ETL processes.
• Ensure Quality: Champion high standards for development, including change management, source control, code reviews, and data monitoring.

What You Need (Must-Haves)

• 4+ years of experience in analytics engineering or data engineering with a focus on data transformation.
• Proven track record of owning data products end-to-end, applying best practices for data quality, scalability, and robust data models.
• Comfort working with ambiguity, collaborating with stakeholders, and taking ownership in a fast-paced environment.
• Experience proactively identifying and implementing improvements to data warehouse performance and ETL efficiency.
• Technical Versatility:
  • Expert-level SQL and dbt skills.
  • Proficiency in Python for transformations.
  • Hands-on experience with query optimization across OLTP and OLAP systems (e.g., Postgres, Iceberg).
  • Proficiency with Semantic Layer modeling (e.g., Cube, dbt Semantic Layer).
  • Experience owning CI/CD workflows and establishing team-wide standards for version control and code review (e.g., Git).
  • Familiarity with cloud environments (GCP or AWS).

Nice to Haves

• Experience with data ingestion tools (e.g., Airbyte) and orchestration tools (e.g., Airflow).
• Domain experience in brokerage operations or a passion for financial markets and modeling financial datasets.

How We Take Care of You

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