Senior Data Engineer @ hubQuest
(práce v Polsku)

Senior Data Engineer @ hubQuest

Polsko

What we expect

• 5+ years of professional experience as a Data Engineer or Software Engineer in data-intensive environments
• Strong Python development skills, with solid understanding of OOP, modular design, and testing (unit/integration)
• Experience with PySpark and distributed data processing frameworks
• Hands-on experience with Azure Data ecosystem, including Databricks, Data Factory, Synapse, and serverless compute
• Solid knowledge of SQL and database performance optimization
• Experience in CI/CD and DevOps practices for data pipelines (GitHub Actions, Azure DevOps, or similar)
• Proven ability to refactor complex systems and implement scalable, automated solutions
• Experience in data testing, validation, and observability frameworks
• Strong communication skills and the ability to work independently in a global, collaborative team environment
• Fluent English

Nice to have

• Experience with DBT (Data Build Tool) for transforming and testing data in analytics pipelines
• Experience with Terraform or other Infrastructure as Code tools
• Familiarity with containerization and orchestration (Docker, Kubernetes)
• Understanding of data governance and metadata management principles
• Experience in multi-tenant or multi-market system design

We are a team of experts bringing together top talents in IT and analytics. Our mission is to build high-performing data and technology teams — from the ground up or by scaling existing ones — to help our partners become truly data-driven organizations.

Currently, we are looking for a Senior Data Engineer to join the Global Analytics Unit, a global, centralized team driving data-driven decision-making and developing smart data products that power everyday operations across markets.

The team’s essence is innovation — we foster a data-first mindset across all business areas, from sales and logistics to marketing and procurement. As the team expands its analytics solutions globally, we’re seeking a hands-on engineer who combines strong software craftsmanship with a passion for building scalable, automated data systems.

Why join us

If you want to:

• Work on complex, large-scale data systems with global impact
• Build robust and scalable data pipelines using modern cloud-native architectures
• Contribute to innovative projects and see your ideas implemented
• Work in a diverse global team of top-tier engineers and data professionals
• Have the freedom to shape tools, technologies, and processes
• Operate in a culture that values autonomy, collaboration, and technical excellence
• ...then this role is for you.

We also offer:

• Flexible working hours and remote work options
• A relaxed, non-corporate environment with no unnecessary bureaucracy
• Private medical care and Multisport card
• A modern office in central Warsaw with great transport links
• Access to global learning resources, certifications, and knowledge exchange

In short

We’re looking for a software-minded Data Engineer — someone who writes clean, testable Python, designs systems that scale globally, and loves automating everything that can be automated. You’ll have a real impact on the architecture and delivery of global analytics solutions used daily across multiple markets.

,[Design, develop, and maintain end-to-end data pipelines and architectures for large-scale analytics solutions, Refactor code and REST services to support dynamic OpCo deployments and multi-tenant scalability, Develop zero-touch deployment pipelines to automate infrastructure and environment provisioning, Implement data validation and testing frameworks ensuring reliability and accuracy across data flows, Integrate new pipelines into a harmonized data execution portal, Build and maintain serverless and Databricks-based data processing systems on Azure, Design and optimize ETL/ELT workflows in Python (including PySpark), Implement Infrastructure as Code (IaC) for reproducible deployments using tools like Terraform, Collaborate closely with Data Scientists, Architects, and Analysts to deliver production-grade data products, Troubleshoot, monitor, and improve data pipelines to ensure performance and resilience] Requirements: Python, Azure, Data engineering, PySpark, Databricks, Azure Data, SQL, dbt, Terraform, Docker, Kubernetes Tools: Agile, Scrum. Additionally: Sport subscription, Private healthcare, Training budget, Small teams, International projects, Free coffee, Bike parking, Free beverages, In-house trainings, In-house hack days, Modern office, No dress code.

Kategorie

data

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