Senior Data Warehouse Engineer

Jobgether; Norway; Remote; NOK 1,427,000 - 1,925,000; Full time

Benefits offered by this job

Fully remote work

Ownership & autonomy

Work with modern data tech

Job summary

Jobgether is seeking a Senior Data Warehouse Engineer based in Norway to shape the data backbone for a high-scale technology platform. You will architect scalable data warehouses, build reliable ELT pipelines, and ensure data accuracy, accessibility, and performance across cloud environments.

The role combines hands-on engineering with collaboration across data science, analytics, and software teams, working in a fully remote, globally distributed setting.

Qualifications

• Extensive experience designing, implementing, and optimizing data warehouses in cloud environments such as AWS or GCP.
• Strong SQL skills and experience with modern columnar data warehouses like ClickHouse, Databricks, BigQuery, or Snowflake.
• Experience with data pipeline orchestration platforms such as Prefect or Airflow.

Responsibilities

• Own key aspects of the data warehouse and pipeline ecosystem to ensure scalable infrastructure and reliable data flows.
• Develop well-documented data pipelines and ELT processes with strong data quality standards.
• Collaborate with analysts, data scientists, and engineers to transform data into actionable insights.

Skills

Data warehousing

SQL proficiency

Cloud data platforms

Collaboration

Independent problem-solving

English communication

Tools

dbt

Prefect

Airflow

ClickHouse

Databricks

BigQuery

Snowflake

Terraform

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Warehouse Engineer based in Norway.

As a Senior Data Warehouse Engineer, you will help shape the data backbone that supports a high-scale technology platform and enables smarter business decisions.
You will architect scalable data warehouses, build reliable pipelines, and ensure data remains accurate, accessible, and performant.
The role combines hands-on engineering with close collaboration across data science, analytics, and software engineering teams.
You will work with modern cloud data technologies and optimize warehouse infrastructure for both performance and cost efficiency.
You will also contribute to developer-facing data tools and establish engineering practices that promote clean, well-structured data.
Working within a globally distributed, fully remote environment, you will have significant ownership and autonomy over your work.
This is an opportunity to make a direct impact on data infrastructure while working with modern technologies across cloud, streaming, transformation, and analytics.

Accountabilities

As a Senior Data Warehouse Engineer, you will own key aspects of the data warehouse and pipeline ecosystem, ensuring scalable infrastructure, reliable data flows, and effective collaboration with teams that depend on high-quality data.

• Architect, build, and maintain scalable, high-performance data warehouse solutions that support analytics and operational needs.
• Develop reliable and well-documented data pipelines and ELT processes while maintaining strong standards for data quality and consistency.
• Design and implement efficient data models and transformations using tools such as dbt and SQL.
• Continuously optimize data warehouse performance through query optimization, partitioning, indexing, and other performance-tuning techniques.
• Monitor, troubleshoot, and improve warehouse infrastructure while balancing performance, reliability, and cost efficiency.
• Partner with data analysts and data scientists to transform raw data into actionable insights and support machine learning initiatives.
• Work with modern cloud-based data warehouse technologies, including ClickHouse and other columnar data platforms.
• Integrate data warehouse capabilities seamlessly with application and service infrastructure.
• Contribute to the development of developer-facing data tools that make data more accessible and useful across engineering teams.
• Establish and promote best practices for data engineering, data quality, documentation, testing, and maintainability.
• Apply software engineering principles such as version control, code reviews, testing, and automation to data infrastructure.
• Support data-driven decision-making by ensuring teams have access to clean, reliable, and well-structured information.
• Collaborate effectively across a globally distributed organization and contribute to a strong engineering culture.

Requirements

The ideal candidate is an experienced data engineer who combines strong technical depth in data warehousing and cloud infrastructure with a collaborative, autonomous approach to solving complex problems.

• Extensive experience designing, implementing, and optimizing data warehouses in cloud environments such as AWS or GCP.
• Strong hands‑on expertise with data modeling and transformation tools, particularly dbt.
• Excellent SQL skills and experience working with modern columnar data warehouses such as ClickHouse, Databricks, BigQuery, or Snowflake.
• Experience with data pipeline orchestration platforms such as Prefect or Airflow.
• Strong understanding of scalable data pipelines, ELT processes, data quality, and warehouse performance optimization.
• Experience with modern software engineering practices, including version control, code reviews, testing, and automation.
• Familiarity with cloud infrastructure and DevOps practices.
• Experience with infrastructure-as-code tools such as Terraform is a plus.
• Scripting or automation experience with Bash, Python, or Go is a plus.
• Familiarity with business intelligence and visualization tools such as Apache Superset, Sigma, Tableau, or Looker is a plus.
• Ability to work independently, take ownership, and make effective decisions in ambiguous environments.
• Strong collaboration skills and the ability to work effectively with data scientists, analysts, and software engineers.
• Excellent English communication skills for working within a globally distributed team.
• Strong problem‑solving mindset and enthusiasm for building scalable, efficient, and maintainable data systems.
• Experience with technologies such as ClickHouse, Redshift, Confluent Kafka, dbt, Prefect, AWS, Terraform, Apache Superset, or Sigma is valuable.
• Must be authorized to work from the location where you reside; visa sponsorship is not available for this position.
• Due to regulatory and security requirements, employment may not be available in certain countries.

Benefits

• US-based cash compensation of $152,000–$205,000.
• Compensation ranges are benchmarked according to role, level, function, and geographic location.
• Fully remote work within the United States.
• Opportunity to work within a globally distributed, 100% remote organization.
• High level of ownership and autonomy in shaping critical data infrastructure.
• Opportunity to work with modern data warehouse, cloud, streaming, orchestration, and infrastructure technologies.
• Cross-functional collaboration with data scientists, analysts, and software engineers.
• Opportunity to contribute to developer-facing tools and data engineering best practices.
• Inclusive and collaborative working environment that values diverse experiences, perspectives, and backgrounds.
• Professional growth through exposure to large-scale data infrastructure and complex engineering challenges.
• Salary offers may vary based on relevant experience, education, certifications, skills, training, and market conditions.