Position Overview

We are seeking a Senior Data Engineer with 4 to 5 years of hands-on experience to design, build, and optimize our data pipelines. Our modern data stack is built on Snowflake (on AWS), utilizing dbt for batch transformations and Python for API integration. In this role, you will not just be a developer; you will have ownership of the data life-cycle, handling everything from real-time streaming data to user-maintained Excel sheets. You will bridge the gap between technical data engineering and business requirements, collaborating occasionally with our global team in Sweden.

Key Responsibilities

1. Pipeline Development & Data Integration

• Design, build, and maintain robust batch and real-time data pipelines integrating diverse data sources: streaming data (e.g., Kafka), structured/semi-structured data (REST APIs), and file-based data (Excel, CSV).
• Develop Python-based integration services using modern serverless architectures (e.g., AWS Lambda) or native platform capabilities (e.g., Snowflake Stored Procedures).

2. Data Modeling & Transformation

• Own the dbt (Data Build Tool) environment to transform raw data into analytics-ready models.
• Design and implement scalable data architectures, specifically focusing on building optimized Gold Layer / Wide Tables that align with downstream Power BI reporting needs.
• Apply best practices in data warehousing, including dimensional modeling (Kimball) and data vaulting where applicable.

3. Optimization & Cloud FinOps

• Monitor, tune, and optimize pipeline performance and query speeds within a cloud environment.
• Implement cost-effective engineering practices to manage and optimize cloud pay-as-you-go expenditures (compute and storage optimization).

4. Business Analysis & Collaboration

• Act as a bridge between business requirements and technical implementation, handling basic Business Analysis (BA) responsibilities to clarify data logic with stakeholders.
• Collaborate with local team members and international colleagues in Sweden to align on data governance and global engineering standards.

Job Requirements Experience & Core Competencies

• 4–5 years of proven, hands-on experience in data engineering or data warehousing roles.
• Strong Data Engineering Sense: Deep understanding of data modeling, ETL/ELT pipeline design, data architecture principles, and performance optimization.
• Cloud Cost Awareness: Experience working within cloud pay-as-you-go frameworks with a mindset geared toward cost-effective development.

Technical Stack (Preferred but not mandatory)

We value strong foundational data engineering skills over specific tool keywords. If you have strong SQL/Python skills and experience with other cloud data warehouses (e.g., BigQuery, Redshift) or ETL tools, we still encourage you to apply.

• Data Platform: Experience with Snowflake hosted on AWS is highly preferred.
• Transformation: Hands-on experience with dbt for regular batch jobs is a significant plus.
• Programming: Strong proficiency in Python (specifically for API integration, AWS Lambda, or writing automated scripts).
• Data Sources: Experience handling real-time streaming (e.g., Kafka), semi-structured data (JSON/XML from APIs), and manual business files (Excel).
• Downstream BI: Basic familiarity or experience with Power BI is a plus—specifically understanding how to structure data layers to optimize Power BI report performance.

Language & Soft Skills

1.Communication: Strong communication skills with the ability to gather business requirements directly from stakeholders.

2.English Proficiency: Solid working English. Native/fluent verbal English is not mandatory, but you must be able to confidently handle basic verbal and written communication with our team in Sweden.

What We Offer

1.An international, inclusive, and flat organizational structure with Swedish company values.

2.Opportunities to work with a modern, cutting-edge data stack (Snowflake, dbt, AWS).

3.Professional growth and clear ownership of projects.

4.Competitive salary and benefits package.