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Alpaca

Senior Analytics Engineer

North America - Remote
Posted about 21 hours ago
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Who We Are:

Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more.

Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 10 million brokerage accounts.

Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of opening financial services to everyone on the planet. We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it.

Alpaca is proudly backed by $400 million in funding from top-tier global investors including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Opera Tech Ventures, SBI Group, Derayah Financial, Unbound, Peak XV, Elefund, and Y Combinator.

Our Team Members:

We're a dynamic team of 400+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond!

We're searching for passionate individuals eager to contribute to Alpaca's rapid growth. If you align with our core values—Stay Curious, Have Empathy, and Be Accountable—and are ready to make a significant impact, we encourage you to apply.

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, which processes hundreds of millions of events daily from a wide array of sources, including transactional databases, API logs, CRMs, payment systems, and marketing platforms.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

You will join our 100% remote team and work closely with Data Engineers (who manage data ingestion) and Data Scientists and Business Users (who consume your data models). Your primary responsibility will be to use dbt and Trino on our GCP-based, open-source data infrastructure to build robust, scalable data models. These models are critical for stakeholders across the company—from finance and operations to the executive team—and are delivered via BI tools, reports, and reverse ETL systems.

What You'll Do:

  • Own the Transformation Layer: Design, build, and maintain scalable data models using dbt and SQL to support diverse business needs, from monthly financial reporting to near-real-time operational metrics.
  • Set Technical Standards: Establish and enforce best practices for data modeling, development, testing, and monitoring to ensure data quality, integrity (up to cent-level precision), and discoverability.
  • Enable Stakeholders: Collaborate directly with finance, operations, customer success, and marketing teams to understand their requirements and deliver reliable data products.
  • Integrate and Deliver: Create repeatable patterns for integrating our data models with BI tools and reverse ETL processes, enabling consistent metric reporting across the business.
  • Ensure Quality: Champion high standards for development, including robust change management, source control, code reviews, and data monitoring as our products and data evolve.

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What You Need (Must-Haves):

  • 4+ years of experience in analytics engineering or data engineering with a strong focus on the "T" (transformation) in ELT.
  • Proven track record of owning data products end-to-end, applying analytics and data engineering best practices to ensure data quality, scalability, and robust data models.
  • Comfortable working with ambiguity and collaborating with stakeholders to define requirements; able to take ownership with minimal oversight 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 for complex queries and data transformations.
    • Proficiency in Python for transformations that extend beyond SQL.
    • Hands-on experience with query optimization across OLTP and OLAP systems (e.g., Postgres, Iceberg).
    • Proficiency with Semantic Layer modelling (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 for brokerage operations or 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

Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce. Recruitment Privacy Policy

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Skills

Analytics engineering
Data engineering
SQL
Dbt
Python
Data modeling
GCP
Trino
CI/CD
Git
Data transformation
Query optimization
Semantic layer
Iceberg
Postgres

Location

East Riding of Yorkshire, England, United Kingdom

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