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SeniorRemoteEurope

Analytics Engineer

A
alpaca
Уровень
Senior
Формат
Remote
О роли

Описание вакансии

About the company

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. Our global team is a diverse group of experienced engineers, traders, and brokerage professionals.

Responsibilities
  • 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.
Requirements
  • 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.
  • 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).
Conditions
  • 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
Стек и навыки

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