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Junior Data Engineer / 1

Summary

Builds scalable streaming data pipelines to replace batch ML workflows, using Kafka, Spark Structured Streaming, Kubernetes, and Python for real-time model inference and monitoring.

Company Description

Inetum Polska is part of the global Inetum Group and plays a key role in driving the digital transformation of businesses and public institutions. Operating in cities such as Warsaw, Poznan, Katowice, Lublin, Rzeszow, Lodz the company offers a wide range of IT services. Inetum Polska actively supports employee development by fully funding training, certifications, and participation in technology conferences. Additionally, the company is involved in local social initiatives, such as charitable projects and promoting an active lifestyle. It prides itself on fostering a diverse and inclusive work environment, ensuring equal opportunities for all.

Key Areas

  • Consulting (Inetum Consulting): Strategic advisory services that help organizations define and implement innovative solutions.
  • Infrastructure and Application Management (Inetum Technologies): Designing and managing IT systems tailored to clients’ individual needs.
  • Software Implementation (Inetum Solutions): Deploying partner solutions from industry leaders like Microsoft, SAP, Salesforce, and ServiceNow.
  • Custom Software Development (Inetum Software): Creating unique software solutions to meet specific client needs.

Flexible And Hybrid Work

Inetum distinguishes itself by offering a comprehensive range of benefits that meet the diverse needs of employees, providing flexibility, support and commitment.

  • Flexible working hours.
  • Hybrid work model, allowing employees to divide their time between home and modern offices in key Polish cities.

Attractive Financial Benefits

  • A cafeteria system that allows employees to personalise benefits by choosing from a variety of options.
  • Generous referral bonuses, offering up to PLN6,000 for referring specialists.
  • Additional revenue sharing opportunities for initiating partnerships with new clients.

Professional Development And Team Support

  • Ongoing guidance from a dedicated Team Manager for each employee.
  • Tailored technical mentoring from an assigned technical leader, depending on individual expertise and project needs.

Community And Well-Being

  • Dedicated team‑building budget for online and on‑site team events.
  • Opportunities to participate in charitable initiatives and local sports programmes.
  • A supportive and inclusive work culture with an emphasis on diversity and mutual respect.

Job Description

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
  • Containerised 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 artefacts 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.

Qualifications

  • 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 containerised 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.

Additional Information

This position offers a hybrid work model. Office location: Warszawa, Poznań, Lublin.

The position includes participation in an on‑call duty.

We hereby inform you that Inetum Polska Sp. z o.o. has implemented an internal reporting (whistleblowing) procedure. The content of the procedure and the possibility to submit an internal report are available at https://inetum.whispli.com/speakup?locale=pl.

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