Junior Data Engineer / 1
Inetum
Junior Data Engineer
We are looking for a Junior Data Engineer to join us and contribute to the development of modern, real‑time data processing capabilities. You will help transition existing data and ML workflows from batch processing to scalable streaming solutions. The role involves hands‑on engineering, close collaboration with Data Scientists, and operational responsibility for production data pipelines.
Technology Environment
- Modern real‑time data streaming technologies used for ML model inference
- Distributed data processing frameworks supporting scalable, low‑latency pipelines
- Containerized workloads orchestrated in cloud‑native environments
- Monitoring and observability tools for ensuring reliability and performance of data pipelines
- Python‑based ecosystem supporting ML model integration and lifecycle management
Key Responsibilities
- Transform batch inference workflows into streaming pipelines
- Define streaming semantics to replace batch windows, including micro‑batching, windowing, and state management
- Design Kafka topic structures, partitioning strategies, and consumer group patterns for prediction workloads
- Implement checkpointing, backpressure handling, and delivery‑guarantee strategies (at‑least‑once / exactly‑once)
- Package and version ML model artifacts for streaming jobs, supporting safe rollouts and rollbacks
- Tune performance for throughput and latency, including batching strategies and resource allocation
- Deploy and operate streaming jobs with monitoring and alerting (lag, throughput, error rates)
- Integrate streaming outputs into downstream ETL/BI systems
- Collaborate with Data Scientists on CI/CD for streaming models and monitor model performance/drift
Team & Collaboration
- You will work in a distributed delivery model closely aligned with the central AI/BI team in Germany
- Daily collaboration through MS Teams, Jira, Confluence
- Agile methodologies (Scrum/Kanban) in cross‑functional squads
Profile
- Practical experience with Kafka (producers/consumers, topic design, partitions, retention)
- Experience with Spark Structured Streaming or similar streaming frameworks
- Familiarity with migrating batch inference to streaming architectures
- Experience running containerized workloads in Kubernetes
- Strong Python skills and understanding of common ML libraries
- English and Polish level B1 or higher
Nice to have
- Basic monitoring/logging experience (ELK, metrics) and performance tuning
- Experience with Kafka Streams
- Familiarity with feature stores or retraining orchestration
Benefits
- Flexible working hours
- Hybrid work model (office in Warsaw, Poznań, Lublin)
- Cafeteria system allowing employees to personalize benefits
- Generous referral bonuses (up to PLN 6,000)
- Additional revenue sharing opportunities for initiating partnerships with new clients
- Ongoing guidance from a dedicated Team Manager for each employee
- Tailored technical mentoring from an assigned technical leader based on expertise and project needs
- Dedicated team‑building budget for online and onsite events
- Opportunities to participate in charitable initiatives and local sports programs
- Supportive and inclusive work culture with emphasis on diversity and mutual respect
Additional Information
This position offers a hybrid work model. Office location: Warszawa, Poznań, Lublin
The position includes participation in an on‑call duty
Location and Contract
Country: Poland
Location: Warsaw
Contract Type: Open‑ended contract
#J-18808-LjbffrOferta pracy dodana 3 dni temu
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