Data Engineering Lead @ hubQuest
(práce v Polsku)

Data Engineering Lead @ hubQuest

Polsko

Must-have skills

• 8+ years in Data Engineering / Software Engineering.
• Proven experience in technical leadership (guiding engineering teams, allocating tasks, setting goals).
• Strong background in Azure cloud data services & technologies.
• Expertise in Azure Databricks, Unity Catalog, Delta Live Tables.
• Strong skills in Data Modelling, ETL pipeline design, and Architecture.
• Excellent programming in Python, PySpark, and SQL (including advanced window functions).
• Hands-on with Azure Data Factory, Azure DevOps CI/CD.
• Understanding of logging, monitoring, and QA/testing practices in DataOps.
• Familiarity with Apache Kafka.
• Solid understanding of the software development lifecycle, including environment separation, role-based access, and testing approaches for scripts and pipelines.
• Knowledge of data quality and testing practices, including automated testing and validation of pipelines.
• Strong communication skills with the ability to translate technical concepts into business language.
• Excellent English communication skills (written & spoken).

Nice-to-have skills

• Azure Synapse, Fabric, PowerBI
• Azure Functions, Azure Logic Apps, Azure API Services
• Microsoft Entra ID
• GCP / AWS exposure
• Azure Networking, Databricks Online Tables
• Jira
• Shell scripting / Azure CLI
• Familiarity with data governance and security concepts (e.g., Unity Catalog policies, RBAC).
• Experience in advanced CI/CD practices for data pipelines (automated tests, integrated monitoring).
• Understanding of Agile at scale frameworks (e.g., SAFe, LeSS) for multi-team collaboration.
• Exposure to data product thinking (datasets and pipelines as reusable, versioned products).

We are a team of tech enthusiasts on a mission to bring together the best minds in IT services and analytics. Our goal? To build cutting-edge IT and Analytical Hubs that empower our partners to become truly data-driven organizations.

For our client’s Data Foundation initiative, we are looking for an experienced Data Engineering Lead who combines strong hands-on engineering skills with technical leadership. In this role, you will spend about 60% of your time developing solutions and 40% guiding the team in engineering practices, setting goals, allocating tasks, and ensuring effective collaboration across squads.

You will report directly to the Engineering Manager and collaborate closely with leaders across global data and technology teams.

What we offer

• Opportunity to shape technical standards and practices within a global technology hub.
• A balanced role: hands-on engineering with technical leadership.
• Work with modern cloud technologies and state-of-the-art data platforms.
• Collaboration across agile squads in a truly international environment.
• Growth opportunities in a rapidly expanding hub.

If you are a pragmatic, collaborative technical leader with a passion for data engineering and modern cloud solutions, we’d love to hear from you!

,[Act as a technical leader for a team of data engineers, ensuring clarity of objectives, task prioritization, and effective resource allocation., Take an active hands-on role (~60%) in building scalable data pipelines, ETL processes, and data solutions., Drive engineering excellence through code reviews, design reviews, testing practices, and deployment processes., Create a safe and collaborative environment for developers, inspiring team members and fostering knowledge sharing across teams., Collaborate with Product Owners, Product Architects, DataOps, QA, and DevOps to translate business needs into robust solutions., Implement and oversee good practices in DataOps, CI/CD, environment separation, and monitoring., Contribute to architectural decisions and solve technical challenges together with your team., Shape and role-model collaborative behaviours, supporting decision-making in complex contexts] Requirements: Python, Azure, Data engineering, Azure Databricks, Unity Catalog, Delta Live Table, Data modelling, ETL, PySpark, SQL, Azure Data Factory, Azure DevOps, DataOps, Apache Kafka, Azure Synapse, Fabric, PowerBI, Azure Functions, Azure Logic Apps, Azure API Services, GCP, AWS, Azure Networking, Databricks Online Tables, Jira, Shell scripting, Azure Cli 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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