Data Engineer - Experimentation Metrics & Pipelines

Super Technologies; España; Presencial; EUR 65.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health Insurance

Open Annual Leave

Employee Assistance Programme

Training & Development

Descripción de la vacante

Super Technologies is seeking a Data Engineer to own the data backbone of the internal Experimentation Platform. You will manage the Metric Store and evaluation data pipelines, spanning Airflow DAGs and Snowflake models to FastAPI services, CI/CD, and integrations with DataHub and the platform UI.

You will deploy services end to end using Docker, Kubernetes, and GitHub Actions, while monitoring with Prometheus and Grafana, and collaborating with backend engineers, data scientists, and product

Formación

• Solid Python engineering with production-ready code and API development (FastAPI or similar).
• Experience with a modern data stack: Airflow, Snowflake, and SQL on large data volumes.
• Production services experience: CI/CD, containerisation, Kubernetes or GitOps; observability.
• Strong data quality mindset and ability to diagnose data discrepancies.
• Clear written communication for RFCs, docs, and async collaboration.

Responsabilidades

• Own and evolve the Metric Store and its API layer.
• Build and maintain evaluation and monitoring pipelines in Airflow on Snowflake.
• Deploy services end-to-end with Docker, Kubernetes, CI/CD, and GitHub Actions.
• Investigate data quality issues, reconcile counts, and validate bucketing and hashing behavior.
• Collaborate with backend engineers, data scientists, and product managers on RFCs and designs.
• Improve developer experience with tooling, exports, and documentation.

Conocimientos

Python engineering

Airflow

Snowflake

FastAPI

CI/CD

Kubernetes

Data quality

SQL debugging

Documentation

Herramientas

Docker

Prometheus

Grafana

GitHub Actions

GitOps

Descripción del empleo

Super Technologies is seeking a Data Engineer to own the data backbone of the internal Experimentation Platform. You will manage the Metric Store and evaluation data pipelines, spanning Airflow DAGs and Snowflake models to FastAPI services, CI/CD, and integrations with DataHub and the platform UI.

You will deploy services end to end using Docker, Kubernetes, and GitHub Actions, while monitoring with Prometheus and Grafana, and collaborating with backend engineers, data scientists, and product