Data Engineer GCP, BigQuery & Analytics - 20180/20185
Veritaz AB · Solna · 6 månader – upp till 12 månader · Deadline 2026-11-18
Veritaz is looking for a **Data Engineer** to join the Store & Sales Analytics team in Solna. The role spans the full data engineering lifecycle, focusing on designing, building, and maintaining scalable, cost-efficient data solutions on Google Cloud Platform, with BigQuery serving as the central data warehouse. Core responsibilities include developing analytical data models and pipelines, optimizing systems for performance and cloud costs, ensuring data quality and traceability, and automating testing, monitoring, and deployments via CI/CD practices. The position also entails contributing to architectural standards and collaborating closely with data analysts to make data accessible across the business. Candidates must have strong hands-on experience with **GCP and BigQuery**, excellent SQL skills, and practical experience using dbt and Python. The role requires proven ability in analytical data modelling, CI/CD automated deployments, Infrastructure as Code (preferably Terraform), and building production-grade solutions with robust monitoring and testing. Applicants must also possess strong collaboration skills and **fluent Swedish**, both spoken and written. Previous experience with Kafka, Google Pub/Sub, REST APIs, Looker or LookML, Node.js or TypeScript, large datasets, and metadata management or observability is considered an advantage.
Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.
Job Overview
Assignment Description
We are seeking an experienced Data Engineer to join the Store & Sales Analytics team in Solna. You will design, develop, and maintain scalable data solutions on Google Cloud Platform (GCP), with BigQuery as the central data warehouse.
The role covers the full data engineering lifecycle, from data ingestion and transformation to data modelling and quality assurance. You will work with dbt, SQL, Python, Terraform, and GitHub Actions to deliver reliable, cost-efficient data pipelines that support analytics, reporting, and business decision-making.
What You Will Work On
- Design, develop, and maintain scalable data pipelines and analytical data models.
- Ensure data quality, reliability, traceability, and consistency.
- Optimise data solutions for performance, scalability, and cost.
- Automate testing, deployments, and monitoring using CI/CD practices.
- Contribute to architecture decisions, technical standards, and development principles.
- Collaborate with Data Analysts and other technical stakeholders to make data accessible and useful.
- Take ownership of solutions from design and development through production deployment and maintenance.
- Build robust production solutions with effective testing, monitoring, and operational reliability.
What You Bring
- Strong hands-on experience with Google Cloud Platform (GCP) and BigQuery.
- Excellent SQL skills.
- Practical experience with dbt.
- Experience with data modelling for analytical use cases.
- Understanding of performance optimisation, cloud costs, and technical trade-offs.
- Experience with CI/CD and automated deployments.
- Experience with Infrastructure as Code, preferably Terraform.
- Experience with Python.
- Experience building production-grade data solutions with data quality checks, testing, monitoring, and reliability.
- Ability to independently analyse problems, propose solutions, and deliver them to production.
- Strong collaboration and communication skills.
- Fluent Swedish, both spoken and written.
Meritorious
- Experience with data ingestion using Kafka, Google Pub/Sub, and/or REST APIs.
- Experience with Node.js or TypeScript.
- Experience with Looker or LookML.
- Knowledge of metadata management, data lineage, and observability.
- Experience working with large datasets and complex data platforms.