Data Engineer

Pyyne Digital; Stockholms kommun; On-site; SEK 450,000 - 600,000; Full time

Job summary

Pyyne Digital is seeking a motivated Data Engineer to build robust data foundations while shaping the company's future. You will design scalable systems and collaborate across industries such as Legal, Green Energy, and MedTech, solving complex data challenges.

Your role will involve building vital infrastructure for AI and analytics, ensuring data quality, and mentoring others. Proficiency in Python, SQL, and experience with data orchestration tools are essential for this opportunity.

Qualifications

• Proficiency in Python and advanced SQL.
• Experience building scalable data pipelines.
• Familiarity with orchestration tools like Airflow.
• Cloud system deployment experience (AWS, Azure, GCP).
• Understanding of ML model lifecycles.

Responsibilities

• Design and build scalable data pipelines.
• Champion data quality and automate testing.
• Collaborate with Data Scientists on ML models.
• Ensure trusted data availability and accessibility.

Skills

Python

SQL

Data pipeline architecture

DataOps practices

Real-time data flows

Education

MSc or BSc in Computer Science, Mathematics, Data Science, or Engineering

Tools

Spark (PySpark)

Kafka

Delta Lake

Snowflake

dbt

Docker

Kubernetes

Terraform

Airflow

Job description

Let's build Pyyne together!

Are you excited by the idea of building robust data foundations while shaping the direction of the company you’re part of? At Pyyne, you’ll do both. We're looking for a motivated Data Engineer to join our consultant team. If you want to take ownership of your projects, build scalable systems, and play an active role in growing an international, people-first tech consultancy, you belong here.

What impact will you have:

As a Data Engineer at Pyyne, you aren't just writing ETL scripts; you are building the vital infrastructure that makes advanced AI and analytics possible. You’ll partner with leaders across industries like Legal, Green Energy, and MedTech to solve complex data challenges, ultimately delivering solutions that reshape Retail and Music Streaming.

You will have a strong voice in strategy, cloud architecture, and data governance. At Pyyne, you are the architect of your career and can choose to dive deep into:

• Modern Data Architecture: Designing and building the robust, scalable pipelines that power enterprise data platforms.

• DataOps & Reliability: Championing data quality, automated testing, and CI/CD to ensure trusted, high-availability data.

• Real-Time & Streaming: Moving beyond batch processing to build event-driven architectures and real-time data flows.

• AI & ML Infrastructure: Collaborating closely with Data Scientists to bridge the gap between raw data and production-ready machine learning models.

About You:

We’re looking for a builder who understands that the best data platforms are created by collaborative teams.

• Systems-Oriented – You care about architecture, scalability, and robustness. You enjoy the "eureka" moment when a complex pipeline runs flawlessly and efficiently in production.

• Curious & Energetic – The data landscape moves fast. You’re excited to experiment with the latest tools (like new modern data stack frameworks) to see if they actually deliver business value.

• Collaborative – You can translate complex backend architectures into clear value for stakeholders and enjoy mentoring others in data engineering best practices.

• Driven & Proactive – You don’t wait for a clean dataset (we know they rarely exist!). You take the initiative to build the processes, transformations, and architecture that make raw data useful.

• Communicative – You’re confident explaining the why behind your technical choices, keeping both tech and business teams aligned.

Your Technical Toolkit:

• Languages: Strong proficiency in Python and advanced SQL.

• Data Engineering: Hands-on experience building and managing scalable pipelines using tools like Spark (PySpark), Kafka, Delta Lake, Snowflake, or dbt.

• Orchestration: Experience with modern data orchestration tools (e.g., Airflow, Dagster, Prefect).

• Cloud & Infrastructure: Experience designing and deploying systems in AWS, Azure, or GCP using Docker, Kubernetes, and Infrastructure as Code (Terraform/Pulumi).

• Bonus Points (Nice to Have):

  • Familiarity with the AI Stack: Understanding of ML model lifecycles and tools like MLflow, Kubeflow, LangChain, or HuggingFace.

  • Analytics Libraries: Experience with Pandas, NumPy, or Dask.

Minimum Qualifications:

• MSc or BSc in Computer Science, Mathematics, Data Science, or Engineering.

• Languages: English (Must), Swedish (Must).