Data Platform Engineer

Type: Contract, per-project. Location: Remote — European Time Zones (CET/CEST) Availability: Contractor (40 hours per week)

We are looking for a Data Platform Engineer to help scale our SaaS platform to support more customers and data. In this role, you will work with data pipelines that transform raw data delivered through APIs into enhanced datasets used by data analysts and data scientists.

This role is ideal for someone who enjoys working in a fast-paced environment and has a strong interest in data engineering, including both developing data pipelines and designing data models.

Expectations for Success

• Participate in the design and help drive the implementation of our data platform based on AWS.
• Design, implement, and operate streaming and batch pipelines that scale.
• Partner with engineers and data analysts to build reliable datasets that can be trusted, understood, and used across the company.

Requirements

• +5 years in a similar role.
• Experience working with data pipelines in AWS.
• Experience with Python.
• Working proficiency with SQL.
• Experience creating and optimizing data models for data analysts using BI tools such as Tableau.
• Experience working in a fast-paced startup environment.
• Prior professional experience building streaming and batch pipelines.
• Experience with DBT or Dataform.
• Familiarity with data orchestration using Apache Airflow.
• Experience with Docker and Kubernetes.
• Experience working with large-scale data pipelines processing approximately 1TB of data per day
• Experience with BigQuery and/or other data warehouse solutions such as Amazon Redshift.
• Ability to explain technical trade-offs and risks in non-technical language.
• Experience creating diagrams and documentation for cross-team alignment.
• Broad experience breaking down high-level system designs into deliverable tasks and providing realistic time and resource estimates.
• Passion for automation and monitoring.

Nice to Have

• Background or experience in the telecommunications industry.
• Machine learning experience.