Azure Data Engineer with DevOps competencies

Azure Data Engineer with DevOps competencies

Wrocław / Kraków / Remote

Regular

B2B: 100 - 140 zł/h
UoP: 13 600 - 17 300 zł brutto

Requirements
/ Your Skills

• You have a very good knowledge of ETL tools and create data processing pipelines
• You can develop data infrastructure diagrams
• You create and document data models
• You can work with Fabric and Azure Data Factory
• You know containerization (Docker) and orchestration (Kubernetes)
• You write scripts freely in Python or Bash
• You have experience working with cloud infrastructure
• You understand what MLOps is and how to manage the ML model lifecycle
• You work well in a team – both with technologists and analysts

Duties
/ Your Role

• You design, implement, and maintain data processing/transformation pipelines
• You build and automate environments for training and deploying ML models – from experiments to monitoring
• You manage cloud infrastructure (mainly Azure, but AWS or GCP is also welcome) and containerization (Docker, Kubernetes)
• You implement and maintain tools for model, data, and code versioning (e.g., MLflow, DVC)
• You monitor system performance and respond to incidents when necessary
• You collaborate with Data Science, ML, and Software Engineering teams to improve deployment processes

Technology Stack
/ Your Expertise

• Fabric
• Azure Data Factory
• Docker
• Kubernetes

At the Data Science team at Univio, we believe that data is the foundation of success in modern business.
Our mission is to support retail companies in their transformation into data-driven organizations, enabling them to fully leverage the potential of their collected information.
We take pride not only in delivering advanced technologies, but most importantly in providing comprehensive solutions to real business problems faced by our clients.

We specialize in key areas related to data and artificial intelligence:
- Data Consulting: We advise clients on data strategy and identify opportunities for leveraging their data.
- Data Science: We conduct advanced data analyses, identify trends and patterns, and draw insights.
- Data Engineering: We design and implement scalable and reliable data pipelines.
- Machine Learning & AI: We build ML models, LLMs, AI assistants, and automate processes.
- Business Intelligence: We design and implement reporting and data visualization systems.

Sounds good to you?
/ Then appply for it!

Katarzyna Chałas
IT Recruitment Specialist

Our Recruitment
/ Process

CV Review - Have you applied? That’s great! We will verify your profile

Let’s get to know each other better - A short phone conversation with a recruiter

An F2F meeting / recruitment task - Share your experience with us - a conversation with a technical person and team leader

Feedback / job offer - We believe in feedback culture - you'll always get a response from us

Individual approach for every candidate

Every role is different. We respond to the needs of each candidate and the position applied for. This way, you get the best recruitment experience and we get the best team members.

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Fast process

Nobody likes waiting around. On average, from initial application to final decision, our process takes around 2 weeks. We make a conscious effort to not keep people in the dark.

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Short decision paths

A quick decision path means less people to complicate the process. From HR to department leaders, this short path results in fast answers and clear decisions.

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Feedback always provided

We appreciate the time, effort and respect every candidate gives us, so we always give feedback to help you progress, regardless of the decision.

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Low percentage of rejected job contracts

Very few of our offers are rejected. Between our long reputation and the engaging projects we can offer, we’re confident we can find the ideal place to help you develop and grow.

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