Data Engineer - 19870
Huy Tran
HR Administrator
Efterfrågade kompetenser
Om tjänsten
Role Summary
An experienced Data Engineer is needed for a consulting assignment within a large, technology-driven automotive organization in Gothenburg. The assignment is situated in a data-intensive environment that uses modern cloud and data technologies to create scalable data solutions and support data-driven products and decision-making.
You will contribute to the development, operation, and continuous improvement of data platforms and pipelines. The role involves close collaboration with Data Engineers, Software Engineers, and both technical and business stakeholders in a technically complex environment.
Key Responsibilities
- Design, develop, maintain, and improve scalable data pipelines and data solutions.
- Develop and manage ETL/ELT processes and data integration workflows.
- Process, transform, and prepare large volumes of data for analytical and product-oriented use cases.
- Build solutions on cloud-based data platforms.
- Contribute to data modelling, data quality, and reliable, efficient data flows.
- Apply CI/CD practices and Infrastructure as Code to support delivery and operational reliability.
- Collaborate with engineering teams and stakeholders to deliver solutions aligned with business and technical needs.
Technical Stack & Requirements
- Programming and query technologies: Python and SQL.
- Cloud and data platforms: Microsoft Azure, Databricks, and Snowflake.
- Data processing technologies: Apache Spark and PySpark.
- Workflow orchestration and transformation: Airflow and dbt.
- Streaming and messaging: Kafka.
- Infrastructure and container technologies: Terraform, Docker, and Kubernetes.
- Version control and delivery tooling: Git and GitHub Actions.
- Data visualisation and monitoring tools: Power BI and Grafana.
Qualifications & Experience
Experience with several of the listed data engineering technologies is highly relevant. The successful consultant should be comfortable working collaboratively in a technically complex environment and contributing across the lifecycle of cloud-based data solutions. The exact technical environment and team-specific requirements will be determined by the receiving team and assignment needs.