Senior Data Engineer

Tenth Revolution Group; Stockholms kommun; Hybrid; SEK 558,000 - 725,000; Full time

Job summary

Tenth Revolution Group in Stockholm, Sweden is seeking a Senior Data Engineer to help evolve the data platform. You’ll work across the data stack from infrastructure to analytics enablement, shaping architecture and building robust data pipelines on a modern cloud environment.

You’ll collaborate with analytics and engineering teams, own end-to-end data solutions, and contribute to AI and automation initiatives while applying strong engineering standards.

Qualifications

• Around 3+ years of experience working in Data Engineering, Data Platform Engineering or a closely related field.
• Strong SQL and Python skills, with experience developing and maintaining production-grade data pipelines and transformations.
• Hands-on experience with a modern cloud data platform, ideally GCP, BigQuery and associated services.
• Experience with dbt, Dataform or similar tools for data transformation, modelling and analytics engineering.
• Worked with orchestration tools such as Airflow or Cloud Composer, ideally building reusable frameworks or managing pipelines at scale.
• Experience with Terraform, Infrastructure as Code, CI/CD or automated deployment processes.
• An understanding of data governance, security, permissions and the importance of building platforms that are scalable, reliable and well managed.
• Taken ownership of technical decisions, improved existing processes or helped establish engineering standards within a team.

Responsibilities

• Building and evolving the data platform: Contribute to the architecture and development of a modern cloud-based data environment.
• Engineering reliable data pipelines: Design, build and optimise data ingestion, transformation and orchestration processes.
• Getting hands-on with GCP: Work with BigQuery, Cloud Composer/Airflow, Pub/Sub and other GCP services.
• Developing data models and frameworks: Use SQL, Python and Dataform/dbt for data models and reusable components.
• Automating infrastructure and deployments: Work with Terraform, CI/CD and IaC to improve reliability.
• Making life easier for other engineers: Build tooling and self-service capabilities for analytics engineers.
• Improving governance, security and performance: Contribute to IAM, data quality and cost optimisation.
• Taking ownership: Identify opportunities to improve solutions and establish engineering best practices.

Skills

GCP

BigQuery

Python

SQL

Dataform/dbt

Terraform

Airflow/Cloud Composer

Tools

Cloud Composer

Airflow

CI/CD

Job description

GCP | BigQuery | Dataform/dbt | Python | Terraform | Stockholm | Hybrid

What if your next Data Engineering role gave you the chance to do more than build pipelines?

We’re working with a fast-moving e-commerce business at a really exciting point in its data journey. The team is evolving its data platform, exploring new ways of working and building the foundations to do even more with data, automation and AI.

There’s plenty to get stuck into, lots of interesting technical challenges to solve, and a genuinely lovely team of people to do it with.

They’re looking for a Senior Data Engineer who enjoys getting under the bonnet of a platform, figuring out how to make things better and taking ownership of the technical solutions they build.

Someone who can move comfortably between data engineering, infrastructure and analytics enablement, and who gets excited by the opportunity to build things properly rather than simply maintain what’s already there.

GCP is their primary cloud environment, but don't rule yourself out if you're coming from AWS or Azure. Strong engineering fundamentals, curiosity and a willingness to get hands-on with new technologies matter far more than having every tool on your CV already.

The role:

Plenty to build, plenty of room to make your mark

You’ll join a collaborative Data team working across the platform, from the underlying infrastructure and orchestration through to the data models and tools that enable the wider business to get more value from its data.

This isn't a role where you'll be handed one small part of the stack and expected to stay in your lane. You'll have the opportunity to influence architecture, improve engineering practices, automate processes and help shape how the platform develops.

Depending on the challenge, you could be designing data pipelines, building reusable orchestration frameworks, improving deployment processes, making data more accessible to analytics teams or helping establish the foundations for new AI and automation use cases.

The common thread? You’ll have the freedom to think about the bigger picture, take ownership and work out the best way to solve the problem.

What you'll be working on

• Building and evolving the data platform: Contribute to the architecture and development of a modern cloud-based data environment, with opportunities to shape how it grows and scales.
• Engineering reliable data pipelines: Design, build and optimise data ingestion, transformation and orchestration processes across a range of sources and systems.
• Getting hands-on with GCP: Work with technologies including BigQuery, Cloud Composer/Airflow, Pub/Sub and other GCP services to build and maintain a robust data platform.
• Developing data models and frameworks: Use SQL, Python and Dataform/dbt to create high-quality data models, reusable components and scalable approaches to data transformation.
• Automating infrastructure and deployments: Work with Terraform, CI/CD and Infrastructure as Code to improve consistency, reliability and the developer experience.
• Making life easier for other engineers: Build tooling and self-service capabilities that help Analytics Engineers and other teams work more independently and efficiently.
• Improving governance, security and performance: Contribute to areas such as IAM, data quality, access controls, cost optimisation and the wider governance of the platform.
• Taking ownership: Identify opportunities to improve existing solutions, challenge how things are done and help establish engineering best practices across the team.
• Exploring what comes next: Help create a scalable data foundation that supports new business requirements, automation initiatives and emerging AI use cases.

There’s a real breadth of work here, so if you enjoy understanding how all the different pieces fit together rather than focusing on one narrow area, you should feel right at home.

The technology

The core environment is built around GCP, with a modern data engineering stack that includes:

There’s also scope to work across infrastructure, automation, data governance and platform architecture.

Ideally, you'll already have hands-on experience with several of these technologies, particularly cloud-based data platforms, SQL, Python, orchestration and Infrastructure as Code.

However, you don't need to tick every box, and GCP experience isn't a deal-breaker.

If you've built data platforms in AWS or Azure, worked with equivalent technologies and understand the underlying principles, your experience could translate really well. They're interested in engineers who understand why they're building something, not just those who know where to click in a particular cloud console.

Who are they looking for?

This would suit an experienced Data Engineer who enjoys combining hands-on technical delivery with broader platform thinking.

You might be someone who has:

• Around 3+ years of experience working in Data Engineering, Data Platform Engineering or a closely related field.
• Strong SQL and Python skills, with experience developing and maintaining production-grade data pipelines and transformations.
• Hands-on experience with a modern cloud data platform, ideally GCP, BigQuery and associated services.
• Experience with dbt, Dataform or similar tools for data transformation, modelling and analytics engineering.
• Worked with orchestration tools such as Airflow or Cloud Composer, ideally building reusable frameworks or managing pipelines at scale.
• Experience with Terraform, Infrastructure as Code, CI/CD or automated deployment processes.
• An understanding of data governance, security, permissions and the importance of building platforms that are scalable, reliable and well managed.
• Taken ownership of technical decisions, improved existing processes or helped establish engineering standards within a team.

Experience mentoring other engineers or taking a technical lead on particular areas of a platform would also be valuable.

You don't need to be an architect, an infrastructure specialist and an analytics engineer all rolled into one. But you should enjoy working across those boundaries, be comfortable taking responsibility for your work and want to understand the platform as a whole.

Perhaps you've built a data platform from scratch. Perhaps you've taken an existing environment and made it significantly more scalable, automated or reliable. Or perhaps you've created the frameworks and tooling that have helped an entire team work better.

What matters is what you've built, the problems you've solved and the way you approach engineering challenges.

The team & environment?

This is one of the particularly appealing parts of the opportunity.

You'll be joining a team that combines interesting technical work with a genuinely collaborative, informal working environment. People are approachable, there's plenty of opportunity to share ideas, and you'll work closely with others rather than disappearing into your own technical silo.

The wider business has a real appetite for data and technology, meaning there are plenty of opportunities to understand business challenges, influence solutions and see the impact of what you build.

It's a great environment for someone who enjoys having ownership without being left to figure everything out alone. You'll have the space to bring ideas to the table, learn from the people around you and help shape how the team works as the platform continues to evolve.

Things move quickly, priorities can change and not every challenge will arrive with a perfectly defined solution. That’s part of the appeal: you'll have the opportunity to get involved, ask questions, experiment and make a tangible difference.

And importantly, this isn't a team where the only thing that matters is getting the code out of the door. They want people who enjoy working together, are curious about what they do and contribute to a positive team atmosphere.

The practical details

• Company: A leading e-commerce business
• Location: Stockholm, Sweden
• Working model: Hybrid, typically 3 days per week in the office
• Language: English is fully workable; Swedish is a plus
• Salary: Around 50,000-65,000 SEK per month, depending on experience, with flexibility for an exceptional profile
• Technology: GCP, BigQuery, Cloud Composer/Airflow, Dataform/dbt, SQL, Python and Terraform
• Team: A collaborative, growing Data team with plenty of scope to influence the platform

Interested?

If you're a Data Engineer who enjoys building things properly, improving how engineering teams work and getting involved in the bigger technical picture, this could be a great next step.

Whether you're already working with GCP or have built your experience in AWS or Azure, we'd love to hear about the platforms you've worked on, the things you've built and the technical challenges you've enjoyed getting stuck into.

If you want a role where you can keep learning, take ownership, work with a great team and help shape a modern data platform, let's have a chat.