📍 Job Overview

Job Title: Data Platform Engineer
Company: MIMIRO
Location: Oslo, Norway & Ås, Norway
Job Type: Full-Time (Hybrid)
Category: Data Engineering
Date Posted: 2025-05-20
Experience Level: Mid-Senior Level (2-5 years)
Remote Status: On-site/Hybrid

🚀 Role Summary

Build and maintain data transformations and pipelines to create valuable data products
Collaborate with cross-functional teams to understand data needs and integrate data from diverse sources
Ensure data quality through automated testing, validation, and monitoring
Develop and deploy SQL and dbt work packages as part of the modern data stack
Manage and document data contracts together with domain experts

📝 Enhancement Note: This role requires a strong focus on data quality, transformation, and integration, with a significant emphasis on collaboration with various teams to meet their data needs.

💻 Primary Responsibilities

Data Transformation & Pipeline Development: Design, build, and maintain data transformations and pipelines using tools like dbt, Airflow, or MLflow to turn raw data into valuable data products.
Data Integration: Integrate data from various sources, including IoT devices, third-party systems, and cloud platforms, ensuring seamless data flow and accessibility.
Data Quality Assurance: Implement automated testing, validation, and monitoring processes to ensure data quality and reliability.
SQL & dbt Development: Develop and deploy SQL and dbt work packages as part of the modern data stack, contributing to the overall data infrastructure and architecture.
Collaboration & Communication: Work closely with R&D, product teams, and application developers to understand their data needs and provide tailored data solutions.
Data Contract Management: Manage and document data contracts together with domain experts, ensuring clear communication and understanding of data requirements and expectations.

🎓 Skills & Qualifications

Education: A degree in computer science or a related engineering field is required.

Experience: 4-5 years of experience working on a production-grade data platform is expected.

Required Skills:

Proficiency in SQL and Python
Hands-on experience with dbt and modern data warehouses like Snowflake
Solid understanding of data platform components and cloud infrastructure (GCP/AWS/Azure)
Experience with Airflow, MLflow, or similar tools is a plus
Strong communication skills and the ability to work independently

Preferred Skills:

Familiarity with IoT devices and data integration from diverse sources
Experience with data quality monitoring and testing tools
Knowledge of agricultural industry data and domain expertise

📝 Enhancement Note: While not explicitly stated, experience with data modeling, ETL processes, and data governance would be beneficial for this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate your ability to transform raw data into valuable insights using dbt, SQL, and other relevant tools.
Showcase your experience with data integration, quality assurance, and monitoring.
Highlight your collaboration skills and ability to work with cross-functional teams to meet their data needs.

Technical Documentation:

Provide examples of well-documented data transformations, pipelines, and data contracts.
Showcase your understanding of data modeling, ETL processes, and data governance through relevant project documentation.
Demonstrate your ability to write clear and concise technical documentation that can be understood by both technical and non-technical stakeholders.

📝 Enhancement Note: While not explicitly stated, a strong portfolio should showcase your ability to translate business needs into technical solutions and communicate complex data concepts effectively.

💵 Compensation & Benefits

Salary Range: The salary range for a mid-senior level data engineer in Norway is typically between 600,000 - 850,000 NOK per year, depending on experience and skills. This estimate is based on regional market research and industry benchmarks.

Benefits:

Personal growth and development opportunities
Competitive salary and benefits package
Modern, interesting tech stack
The chance to contribute to sustainable agriculture for the future
Insight into Norwegian agriculture and food production
A friendly, down-to-earth team committed to making a difference

Working Hours: The standard working hours are 40 hours per week, with flexibility to work from the Oslo or Ås office, or from home when needed.

📝 Enhancement Note: The salary range provided is an estimate based on market research and may vary depending on the candidate's skills, experience, and the company's internal salary structure.

🎯 Team & Company Context

🏢 Company Culture

Industry: MIMIRO operates in the agri-tech industry, focusing on improving agriculture through technology.

Company Size: MIMIRO is a small to medium-sized company with around 32 employees, providing ample opportunities for growth and impact.

Founded: MIMIRO was established as a joint venture startup in 2021, with ownership from Tine SA, Felleskjøpet Agri, and Gjensidige.

Team Structure:

The data team works closely with R&D, product teams, and application developers to meet their data needs.
The team enjoys a high degree of autonomy and collaboration, with a focus on translating business needs into technical solutions.

Development Methodology:

MIMIRO uses modern data stack technologies like dbt, Snowflake, and cloud infrastructure (GCP/AWS/Azure) for data transformation, storage, and processing.
The team follows Agile methodologies, with a focus on continuous integration, deployment, and improvement.

Company Website: Open MIMIRO

📝 Enhancement Note: MIMIRO's company culture emphasizes collaboration, innovation, and a strong focus on sustainable agriculture, providing an excellent environment for data engineers to grow and make a significant impact.

📈 Career & Growth Analysis

Data Engineering Career Level: This role is at the mid-senior level, with a focus on data transformation, integration, and quality assurance. The ideal candidate will have 4-5 years of experience working on a production-grade data platform and be ready to take on more complex challenges and leadership responsibilities.

Reporting Structure: The data engineer will report directly to the CTO and work closely with the data team, R&D, product teams, and application developers.

Technical Impact: The data engineer will play a crucial role in ensuring data quality, accessibility, and reliability across the organization. Their work will directly impact the performance and success of MIMIRO's applications and sustainability efforts.

Growth Opportunities:

Technical Growth: Expand your skills and expertise in data transformation, integration, and quality assurance, with opportunities to learn and work with modern data stack technologies.
Leadership Development: As the team grows, there will be opportunities to take on more leadership responsibilities, mentoring junior team members and driving data strategy and architecture decisions.
Career Progression: With experience and proven success, there may be opportunities to move into more senior roles within the data team or the organization.

📝 Enhancement Note: MIMIRO's focus on sustainable agriculture and data-driven decision-making provides ample opportunities for data engineers to grow technically, lead projects, and make a significant impact on the organization's success.

🌐 Work Environment

Office Type: MIMIRO offers a hybrid work environment, with offices in downtown Oslo and Ås, and the flexibility to work from home when needed.

Office Location(s):

Spaces - Oslo, Spaces Apotekergata, 0180 Oslo, Norway
Raveien 2b, 1430 Ås, Norway

Workspace Context:

The offices provide modern, collaborative workspaces with access to the latest tools and technologies.
The team enjoys a high degree of autonomy and flexibility, with a focus on results and impact.
MIMIRO's team is diverse, with members from various backgrounds and locations, fostering a global and inclusive work environment.

Work Schedule: The standard working hours are 40 hours per week, with flexibility to work from the Oslo or Ås office, or from home when needed.

📝 Enhancement Note: MIMIRO's hybrid work environment and flexible scheduling provide an excellent balance between collaboration and autonomy, allowing data engineers to thrive both personally and professionally.

📄 Application & Technical Interview Process

Interview Process:

Initial Screening: A brief phone or video call to discuss your experience, skills, and motivation for the role.
Technical Assessment: A hands-on technical assessment, focusing on your data transformation, integration, and quality assurance skills. This may include tasks such as designing and implementing data pipelines, writing SQL queries, or working with dbt.
Team Fit & Culture: A conversation with the data team and other stakeholders to assess your cultural fit and alignment with MIMIRO's values.
Final Evaluation: A final discussion with the CTO to review your technical assessment, team fit, and answer any remaining questions.

Portfolio Review Tips:

Highlight your experience with data transformation, integration, and quality assurance using relevant tools and technologies.
Showcase your ability to work with cross-functional teams and translate business needs into technical solutions.
Demonstrate your understanding of data modeling, ETL processes, and data governance through relevant project examples.

Technical Challenge Preparation:

Brush up on your SQL and Python skills, with a focus on data transformation, integration, and quality assurance.
Familiarize yourself with modern data stack technologies like dbt, Snowflake, and cloud infrastructure (GCP/AWS/Azure).
Prepare for questions about data modeling, ETL processes, and data governance, as well as your experience working with cross-functional teams.

ATS Keywords: [Comprehensive list of data engineering, SQL, Python, dbt, Snowflake, cloud infrastructure (GCP/AWS/Azure), data modeling, ETL, data governance, and team collaboration keywords]

📝 Enhancement Note: MIMIRO's interview process focuses on assessing your technical skills, cultural fit, and alignment with the organization's mission and values, providing an excellent opportunity to showcase your expertise and passion for data engineering.

🛠 Technology Stack & Web Infrastructure

Data Transformation & Integration Tools:

dbt: A data transformation tool used to turn raw data into valuable data products.
Snowflake: A modern data warehouse for storing and processing large datasets.
Airflow & MLflow: Tools for orchestrating and managing data pipelines and machine learning workflows.
Cloud Infrastructure (GCP/AWS/Azure): Cloud-based infrastructure for data storage, processing, and deployment.

Data Quality & Monitoring Tools:

Various tools for automated testing, validation, and monitoring, such as Great Expectations, DataDog, or Prometheus.

📝 Enhancement Note: MIMIRO's technology stack focuses on modern data stack technologies, providing an excellent environment for data engineers to work with cutting-edge tools and technologies.

👥 Team Culture & Values

Data Engineering Values:

Responsibility: Take ownership of data quality, transformation, and integration, ensuring data reliability and accessibility.
Collaboration: Work closely with cross-functional teams to understand their data needs and provide tailored data solutions.
Innovation: Continuously learn and explore new data transformation, integration, and quality assurance techniques and tools.
Sustainability: Contribute to MIMIRO's mission of improving agriculture through technology and promoting sustainable practices.

Collaboration Style:

Cross-functional Integration: Work closely with R&D, product teams, and application developers to understand their data needs and provide tailored data solutions.
Code Review Culture: Collaborate with the data team to review and improve data transformations, pipelines, and quality assurance processes.
Knowledge Sharing: Share your expertise and learn from others in a collaborative and inclusive work environment.

📝 Enhancement Note: MIMIRO's data engineering values and collaboration style emphasize responsibility, collaboration, innovation, and sustainability, providing an excellent environment for data engineers to grow both personally and professionally.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Integration: Integrate data from various sources, including IoT devices, third-party systems, and cloud platforms, ensuring seamless data flow and accessibility.
Data Quality: Ensure data quality through automated testing, validation, and monitoring, with a focus on data reliability and accessibility.
Data Modeling: Design and implement data models that efficiently store and process large datasets, with a focus on performance and scalability.
Emerging Technologies: Stay up-to-date with emerging data transformation, integration, and quality assurance techniques and tools, and explore their potential application within MIMIRO's data stack.

Learning & Development Opportunities:

Technical Skill Development: Expand your skills and expertise in data transformation, integration, and quality assurance, with opportunities to learn and work with modern data stack technologies.
Conference Attendance & Certification: Attend industry conferences and obtain relevant certifications to stay up-to-date with the latest trends and best practices in data engineering.
Technical Mentorship: Benefit from the expertise and guidance of experienced data engineers within MIMIRO and the broader data engineering community.

📝 Enhancement Note: MIMIRO's technical challenges and learning opportunities provide an excellent environment for data engineers to grow both technically and professionally, with a strong focus on collaboration, innovation, and sustainability.

💡 Interview Preparation

Technical Questions:

Data Transformation & Integration: Describe your experience with data transformation, integration, and quality assurance, with a focus on tools like dbt, Snowflake, Airflow, and MLflow.
Data Modeling & ETL: Explain your approach to data modeling, ETL processes, and data governance, with examples from previous projects.
Cloud Infrastructure: Discuss your experience with cloud infrastructure (GCP/AWS/Azure) and data storage, processing, and deployment.
Data Quality & Monitoring: Describe your experience with data quality monitoring, automated testing, and validation, with a focus on ensuring data reliability and accessibility.

Company & Culture Questions:

MIMIRO's Mission: Explain why you are excited about MIMIRO's mission to improve agriculture through technology and promote sustainable practices.
Team Dynamics: Describe your experience working with cross-functional teams and your approach to collaboration, communication, and knowledge sharing.
Data-Driven Decision-Making: Discuss your experience with data-driven decision-making and your ability to translate data insights into actionable business recommendations.

Portfolio Presentation Strategy:

Data Transformation & Integration: Highlight your experience with data transformation, integration, and quality assurance using relevant tools and technologies.
Data Modeling & ETL: Showcase your approach to data modeling, ETL processes, and data governance through relevant project examples.
Cross-Functional Collaboration: Demonstrate your ability to work with cross-functional teams and translate business needs into technical solutions.
Data-Driven Decision-Making: Highlight your experience with data-driven decision-making and your ability to translate data insights into actionable business recommendations.

📝 Enhancement Note: MIMIRO's interview process focuses on assessing your technical skills, cultural fit, and alignment with the organization's mission and values, providing an excellent opportunity to showcase your expertise and passion for data engineering.

📌 Application Steps

To apply for this data engineering position at MIMIRO, follow these steps:

Tailor Your Resume: Highlight your experience with data transformation, integration, and quality assurance, as well as your ability to work with cross-functional teams and translate business needs into technical solutions.
Prepare Your Portfolio: Showcase your experience with data transformation, integration, and quality assurance using relevant tools and technologies, with a focus on data modeling, ETL processes, and data governance.
Practice Technical Challenges: Brush up on your SQL and Python skills, with a focus on data transformation, integration, and quality assurance. Familiarize yourself with modern data stack technologies like dbt, Snowflake, and cloud infrastructure (GCP/AWS/Azure).
Research MIMIRO: Learn about MIMIRO's mission, values, and technology stack, and prepare thoughtful questions to ask during your interviews.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and data engineering industry-standard assumptions. All details should be verified directly with MIMIRO before making application decisions.

Data Platform Engineer