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We are searching for a talented Data Engineer with solid experience in building and supporting modern cloud-based data platforms.
The ideal candidate brings hands-on expertise with Google BigQuery, Python, and Apache Airflow, and takes genuine interest in crafting scalable data pipelines, refining data processing workflows, and empowering data-driven decision-making throughout the organization. The right person will feel at home in an Agile setting, teaming up with data analysts, software engineers, product teams, and stakeholders to produce dependable and efficient data solutions. We appreciate proactive individuals who show ownership, sharp problem-solving skills, and a continuous improvement outlook.
- Architect, build, and support scalable data pipelines along with ETL/ELT processes
- Construct and refine data solutions leveraging Google BigQuery
- Create data processing and automation workflows with Python
- Set up, schedule, monitor, and diagnose workflows using Apache Airflow
- Safeguard data quality, reliability, and consistency across a variety of data sources
- Fine-tune query performance, storage usage, and overall platform efficiency
- Work with business and technical stakeholders to capture data requirements and turn them into scalable solutions
- Put in place monitoring, alerting, and operational best practices for data pipelines
- Contribute to data governance, security, and compliance initiatives
- Add to technical documentation, knowledge sharing, and engineering best practices
- Take part in code reviews, design discussions, and Agile ceremonies
- No less than 2 years of professional relevant experience in data engineering
- Strong background in Python development for data engineering and automation activities
- Applied experience with Google BigQuery, including data modeling, performance tuning, and query optimization
- Practical background in designing and supporting Apache Airflow workflows
- Solid grasp of ETL/ELT concepts and modern data architectures
- Confident SQL skills with hands-on experience handling large-scale datasets
- Track record of integrating data from a variety of sources such as APIs, databases, and cloud services
- Understanding of data warehousing concepts and dimensional modeling
- Working experience with version control systems such as Git
- Familiarity with CI/CD practices and deployment automation
- Strong analytical thinking and troubleshooting abilities
- Good communication skills together with the ability to collaborate effectively within cross-functional teams
- Background working in Agile/Scrum environments
- English at B2 level or higher, with strong written and spoken communication skills
- Familiarity with data orchestration, observability, and monitoring tools
- Practical experience with containerization technologies such as Docker
- Exposure to machine learning data pipelines or MLOps concepts
- Applied use of AI-assisted development tools such as GitHub Copilot, Gemini, or similar solutions