Junior Data Engineer / 1

Inetum; Warsaw (IN); Hybrid; USD 24,000 - 35,000; Full time

Benefits offered by this job

Hybrid work model

Cafeteria benefits

Up to PLN6,000 referral bonuses

Revenue sharing opportunities

Dedicated team mentoring

Job summary

Inetum Polska is seeking a Junior Data Engineer to help transform batch inference workflows into streaming pipelines, enabling real-time data processing for ML models. You will work closely with Data Scientists, be responsible for production data pipelines, and operate in a distributed delivery model with the central AI/BI team in Germany.

This hybrid role based in Warszawa/Poznań/Lublin offers exposure to Kafka, Spark Structured Streaming, Kubernetes, and Python, with collaboration via MS

Qualifications

• Experience with Kafka and streaming pipelines in production.
• Hands-on with Spark Structured Streaming or similar.
• Experience migrating batch inference to streaming architectures.
• Experience with containerized workloads in Kubernetes.
• Strong Python skills and ML libraries.
• English and Polish at least B1 level.

Responsibilities

• Transform batch inference workflows into streaming pipelines.
• Define streaming semantics: micro-batching, windowing, state management.
• Design Kafka topic structures, partitions, and consumer groups for prediction workloads.
• Implement checkpointing, backpressure, and delivery guarantees (at-least-once / exactly-once).
• Package and version ML model artifacts for streaming jobs, supporting rollouts/rollbacks.
• Tune performance for throughput and latency, including batching strategies and resource allocation.
• Deploy and operate streaming jobs with monitoring and alerting (lag, throughput, errors).
• Integrate streaming outputs into downstream ETL/BI systems.
• Collaborate with Data Scientists on CI/CD for streaming models and monitor performance/drift.
• Work in a distributed delivery model with the central AI/BI team in Germany.
• Daily collaboration via MS Teams, Jira, Confluence.

Skills

Kafka

Spark Structured Streaming

Python

Kubernetes

English/Polish B1+

Tools

Jira

Confluence

Kubernetes

CI/CD tools

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
• 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.
• 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.

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 Polishlevel 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.

About Inetum

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.

Globally, Inetum operates in 19 countries and employs over 28,000 professionals. The company focuses on four key areas:

Consulting

Strategic advisory services that help organizations define and implement innovative solutions.

Infrastructure and Application Management

Designing and managing IT systems tailored to clients’ individual needs.

Software Implementation

Deploying partner solutions from industry leaders like Microsoft, SAP, Salesforce, and ServiceNow.

Custom Software Development

Creating unique software solutions to meet specific client needs.

With strategic partnerships with major technology giants, including Microsoft, SAP, Salesforce, and ServiceNow, Inetum delivers advanced technological solutions tailored to customer requirements. In 2023, Inetum reported revenues of €2.5 billion, underscoring its strong position in the digital services market.

Flexible and hybrid work

• 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 personalize 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 programs.
• A supportive and inclusive work culture with an 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.

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