Senior Data Engineer
@ Foodello - Fiksuruoka.fi

Helsinki, Uusimaa, Finland
€80,000
On Site
Full Time
Posted 1 day ago

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Job Details

Overview

At Foodello - Fiksuruoka.fi, fight food waste and drive company growth as a Senior Data Engineer. You will develop and maintain our data infrastructure, ensuring integrity and seamless integrations between our source systems and Snowflake Data Cloud.

What You’ll Do

  • Implement and maintain robust data ingestion pipelines for scalable growth
  • Maintain and improve data infrastructure including pipelines, storage, orchestration, and DevOps
  • Collaborate with stakeholders and analytics engineers to deliver effective data integrations
  • Develop and maintain reverse-ETL processes for business-critical data

Our Tech Stack & Methodology

Work with Terraform, GCP, Fivetran, dbt on Snowflake, Dagster, and Tableau, following DataOps principles like automation, testing, and continuous improvement.

What We’re Looking For

  • Extensive experience in data engineering with production-grade data systems
  • High proficiency in SQL and Python
  • Proactive, organized, and capable of taking ownership
  • Effective communicator with a collaborative spirit
  • Based in Finland (no relocation support available)

Why Join Us?

  • Data at the core of fighting food waste
  • Ownership, learning, and professional growth are guaranteed
  • True work-life balance with flexible hybrid work options

About the Company

Foodello - Fiksuruoka.fi is a purpose-driven scale-up combating food waste. With locations in Helsinki and Amsterdam, we save millions of kilos of food annually and continuously innovate in data-driven decision making.

Key Skills/Competency

  • Data Engineering
  • SQL
  • Python
  • Data Pipelines
  • Snowflake
  • DataOps
  • Terraform
  • GCP
  • ETL/ELT
  • Collaboration
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How to Get Hired at Foodello - Fiksuruoka.fi

🎯 Tips for Getting Hired

  • Research Foodello - Fiksuruoka.fi: Understand the company mission and culture.
  • Tailor your resume: Highlight data engineering projects and tools.
  • Showcase SQL and Python skills: Provide specific examples.
  • Prepare for technical interviews: Review data pipeline architectures and DataOps principles.
  • Network on LinkedIn: Reach out to current employees for insights.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query optimization techniques.
Practice Python data manipulation scripts.
Study Snowflake architecture and integration.
Brush up on infrastructure automation with Terraform.

Behavioral Questions

Describe past ownership of complex projects.
Explain team collaboration experiences in data roles.
Share problem-solving approaches under pressure.
Discuss adapting to change in fast environments.

Frequently Asked Questions