Remote Analytics Transformation Engineer

Alpaca; España; Remote; EUR 88.000 - 123.000; Vollzeit

Benefits dieser Stelle

Salary & stock options

Health benefits

Home-office setup

Monthly stipend

Zusammenfassung

Alpaca is seeking an Analytics Engineer to own the transformation layer of our data platform. You’ll work with dbt and Trino on a GCP-based open-source stack, delivering scalable models used by finance, operations, and executives via BI tools and reverse ETL.

You will join a 100% remote team, collaborating with data engineers, scientists, and business users to ensure high-quality, reliable data products across the company.

Qualifikationen

• 4+ years in analytics or data engineering focused on data transformation.
• Ownership of data products end-to-end with quality and scalability focus.
• Ability to work with ambiguity and deliver with minimal oversight.
• Experience improving data warehouse performance and ETL efficiency.
• Strong SQL and dbt skills for complex transformations; Python for extra logic.
• Experience with Postgres, OLAP/Iceberg, and cloud environments (GCP/AWS).

Aufgaben

• Own the transformation layer using dbt and SQL for diverse business needs.
• Set standards for data modelling, development, testing, and monitoring.
• Collaborate with finance, operations, and marketing to deliver data products.
• Create patterns for BI integration and reverse ETL to ensure consistent metrics.
• Maintain high development standards, including version control and code reviews.

Kenntnisse

Analytics engineering

Data transformation

SQL

DBT

Python

PostgreSQL

Iceberg

Semantic Layer

CI/CD

Git

Tools

Airbyte

Airflow

dbt Semantic Layer

Git

Jobbeschreibung

Alpaca is seeking an Analytics Engineer to own the transformation layer of our data platform. You’ll work with dbt and Trino on a GCP-based open-source stack, delivering scalable models used by finance, operations, and executives via BI tools and reverse ETL.

You will join a 100% remote team, collaborating with data engineers, scientists, and business users to ensure high-quality, reliable data products across the company.