Dataflow Engineer

At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe. Are you passionate about building robust, scalable data pipelines that power analytics and decision-making? We are looking for a Dataflow Engineer to design, develop, and maintain efficient data workflows that ensure seamless data movement across systems. Sounds like your kind of challenge? #Li-Hybrid - Hybrid work model: 2 days per week from the office in Kraków What you get in return Flexible cooperation model – choose the form that suits you best (B2B, employment contract, etc.) Hybrid work setup – remote days available depending on the client’s arrangements Collaborative team culture – work alongside experienced professionals eager to share knowledge Continuous development – access to training platforms and growth opportunities Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more High quality equipment – laptop and essential software provided
Requirements:
Experience: 4+ years as a Dataflow Engineer, Data Engineer, or similar role working with large datasets and distributed systems. Technical Skills: Proficiency in Python and/or Java. Hands-on experience with data pipeline orchestration tools (e.g., Google Dataflow ). Strong knowledge of Google Cloud services ( BigQuery, Dataflow ). Expertise in ETL frameworks , real-time data streaming, and processing. Familiarity with data formats like JSON, Parquet. Knowledge of SQL and NoSQL databases , data governance, and security best practices. Other Skills: Strong problem-solving abilities for complex data integration issues. Excellent communication skills for collaboration with technical and non-technical stakeholders. Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.
Must have: Python, Java, Google Cloud, BigQuery, ETL, JSON, SQL, NoSQL, Security
Daily tasks: - Design and Build Data Pipelines: Develop and implement efficient pipelines for collecting, transforming, and storing data across multiple platforms.
– Data Integration: Integrate data from diverse sources, including cloud platforms (Google Cloud), databases (SQL/NoSQL), APIs, and external services.
– Optimize Data Flow: Troubleshoot and fine-tune existing pipelines for optimal performance.
– Data Transformation: Implement ETL processes to convert raw data into analytics-ready formats.
– Collaboration: Work with cross-functional teams to understand data needs and provide solutions; support applications during weekends or non-office hours when needed.
– Automation & Scalability: Build scalable, automated workflows to handle large data volumes with high reliability and low latency.
– Monitoring & Maintenance: Set up monitoring and alerting systems to ensure minimal downtime and maximum performance.
– Documentation: Maintain clear documentation of data flows, pipeline configurations, and processing logic.