Senior Data Engineer
Aurora Engineering AB · Gothenburg, Sweden
IT Services and IT Consulting · 11-50 employees
About the role
Design, develop, and maintain scalable batch and streaming data pipelines and cloud-based data platforms. Collaborate with stakeholders to build data models and dashboards that enable data-driven decision-making.
What they look for
Requirements
Requires a degree in Computer Science or a related field and at least 5 years of experience in data engineering. Proficiency in Big Data technologies, SQL, Python, and cloud platforms like AWS or Azure is essential.
Full description
We are looking for an experienced Senior Data Engineer to join our Cloud Platform & Data team. In this role, you will design, develop, and maintain scalable data pipelines and cloud-based data platforms that support secure data sharing and analytics. You will work with modern big data technologies to build reliable data solutions, optimize platform performance, and enable data-driven decision-making across the organization.
Key Responsibilities
- Design, develop, and maintain scalable batch and streaming data pipelines.
- Build and optimize ETL/ELT processes for ingesting, transforming, and preparing data.
- Develop data processing workflows, including cleansing, deduplication, and transformation.
- Operate, monitor, and maintain cloud-based data platforms in collaboration with infrastructure teams.
- Perform regression, functional, and security testing following platform upgrades.
- Ensure data quality, integrity, consistency, and security through validation and monitoring.
- Troubleshoot and resolve issues related to data pipelines, storage, and integrations.
- Collaborate with business stakeholders to define data models and support reporting requirements.
- Provide technical guidance and secure data access to internal data consumers.
- Design and maintain data models for analytics and reporting.
- Develop dashboards and reports using Power BI.
- Document data architectures, pipelines, and technical workflows.
- Support DevOps, CI/CD, and Infrastructure as Code (IaC) practices for data platform management.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
- Minimum 5 years of experience in Data Engineering.
- Strong experience with Big Data technologies such as Apache Spark, Kafka, Flink, and Data Lakes.
- Strong understanding of Data Warehousing, ETL/ELT processes, and data modeling.
- Experience with SQL and Python programming.
- Hands-on experience with AWS services such as S3, EMR, and Redshift.
- Experience with Azure Data Factory and Power BI.
- Experience with Databricks and/or Snowflake.
- Good knowledge of DevOps, CI/CD pipelines, and software testing.
- Experience building scalable cloud-based data platforms.
- Excellent analytical and problem-solving skills.
- Strong communication skills in English.
Preferred Qualifications
- Experience with Infrastructure as Code (IaC), such as Terraform or CloudFormation.
- Experience with automotive or connected vehicle data platforms.
- Experience with streaming data architectures.
- Chinese language skills are an advantage.
Technical Skills
- Data Engineering
- Apache Spark
- Apache Kafka
- Apache Flink
- Data Lakes
- ETL / ELT
- SQL
- Python
- AWS (S3, EMR, Redshift)
- Azure Data Factory
- Databricks
- Snowflake
- Power BI
- Data Warehousing
- Data Modeling
- DevOps
- CI/CD
- Infrastructure as Code (IaC)
Key Competencies
- Data Pipeline Development
- Cloud Data Platforms
- Data Quality Management
- Performance Optimization
- Problem Solving
- Analytical Thinking
- Stakeholder Collaboration
- Communication
- Documentation
- Continuous Improvement!
