Data Engineer Poland

Zoolatech; Wrocław; On-site; PLN 120,000 - 180,000; Full time

Job summary

A global jewelry manufacturer is seeking a Data Engineer to design and implement scalable data products using Azure PaaS technologies. The ideal candidate will have 3-5 years of experience, strong skills in Python and SQL, familiarity with Azure Synapse and Databricks, and the ability to collaborate effectively in cross-functional teams. This role offers an opportunity to play a key part in driving data-driven decision-making across the organization.

Qualifications

• 3-5 years of experience as a Data Engineer.
• Strong track record of delivering production-ready data products.
• Familiarity with cloud platforms (AWS, Azure, or GCP).

Responsibilities

• Design, develop, and maintain scalable ETL processes and data pipelines.
• Collaborate with teams to translate business requirements into solutions.
• Ingest, transform, and optimize large data sets.

Skills

Python

SQL

Data Engineering

ETL processes

Data Analytics

Problem-solving

Communication

Tools

Azure Synapse Analytics

Databricks

PySpark

PostgreSQL

MySQL

MongoDB

Job description

Our client is a global jewelry manufacturer undergoing a major transformation, moving from IaaS-based solutions to a modern Azure PaaS data platform. As part of this journey, you will design and implement scalable, reusable, and high-quality data products using technologies such as Data Factory, Data Lake, Synapse, and Databricks. These solutions will enable advanced analytics, reporting, and data-driven decision-making across the organization. By collaborating with product owners, architects, and business stakeholders, you will play a key role in maximizing the value of data and driving measurable commercial impact worldwide.

Design, develop, and maintain scalable ETL processes and data pipelines.

Collaborate with product owners, architects, and cross-functional teams to translate business and product requirements into technical solutions.

Ingest, transform, and optimize large, complex data sets while ensuring data quality, reliability, and performance.

Ensure data integrity, quality, and consistency through rigorous testing and validation.

Optimize data storage, retrieval, and processing for performance and scalability.

Apply DevOps practices, CI/CD pipelines, and coding best practices to ensure robust, production-ready solutions.

Document technical specifications, data models, and system architecture for team alignment and long-term maintainability.

Contribute to a culture of innovation by following best practices while exploring new ways to push the boundaries of data engineering.

3-5 years of experience as a Data Engineer, with a strong track record of designing, building, and delivering production-ready data products at enterprise scale.

Proficiency in Python, SQL, and relevant programming languages.

Practical experience with Azure Synapse Analytics, Databricks, and PySpark.

Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform).

Solid understanding of ETL processes, data warehousing, and database management (PostgreSQL, MySQL, MongoDB, etc.).

Ability to design and implement data models for transactional and analytical systems.

Strong analytical thinking and problem-solving skills.

Excellent communication skills to work effectively in cross-functional teams.

Attention to detail, adaptability, and a collaborative mindset.

Leadership or mentoring experience is a plus.