Data Engineer
Ledgy
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇩🇪 Germany
Visit company websiteJob Level
JuniorMid-Level
Tech Stack
BigQueryCloudETLGoogle Cloud PlatformPandasPythonSQL
About the role
- Manage and optimize data infrastructure and ETL pipelines using Fivetran, Airbyte, and Google Cloud Platform, ensuring reliable data flow from multiple sources into our analytics ecosystem
- Develop, test, and maintain DBT models that transform raw data into analytics-ready datasets following best practices
- Create and manage LookML models in Looker to enable self-service analytics for stakeholders across the company
- Drive continuous improvement of our data engineering practices, tooling, and infrastructure as a key member of the Operations team
Requirements
- 2-3+ years experience building production data pipelines and analytics infrastructure, with DBT, SQL, and Python (Pandas, etc.)
- Experience implementing and managing ETL/ELT tools such as Fivetran or Airbyte
- Ideally hands-on experience with GCP (BigQuery)
- Proficiency in Looker, including LookML development
- Strong plus if you have experience using n8n or similar automation tools
- Experience with SaaS data sources (HubSpot, Stripe, Vitally, Intercom)
- Familiarity with AI-powered development tools (Cursor, DBT Copilot) and a strong interest in leveraging cutting-edge tools to improve workflow
- Strong problem-solving skills and ability to debug complex data issues
- Excellent communication skills with ability to explain technical concepts to non-technical stakeholders.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
DBTSQLPythonETLELTLookMLdata pipelinesdata infrastructureanalyticsdata transformation
Soft skills
problem-solvingcommunication