Data Engineer 2
Company: Cencora
Role summary
Data Engineer 2 is a full-time role at Cencora in Lublin, Lublin Voivodeship, Poland (on-site). Posted 2026-10-09. Experience level: 5-10. No degree required.
- Job title
- Data Engineer 2
- Company
- Cencora
- Location
- Lublin, Lublin Voivodeship, Poland
- Work arrangement
- on-site
- Employment type
- full-time
- Category
- Data Science
- Experience level
- 5-10
- Degree required
- No
- Date posted
- 2026-10-09
This full-time Data Engineer role at Cencora offers a fantastic opportunity to contribute to a mission-driven company focused on healthier futures for people and animals. You won't need a degree to join their innovative team and help build crucial data solutions, with a competitive salary and growth potential for experienced professionals.
Job description
Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today!
Job Details
Purpose Summary
To design, build, support and maintain scalable, reliable data solutions that enable the business to make timely, data-driven decisions. This role owns the data pipelines, integrations and analytics tooling — including Snowflake and Power BI — that underpin reporting and analytics across the organisation, working closely with the Development, Cloud and Security engineering teams to ensure data solutions are delivered securely, reliably and efficiently. The role is forward-looking, embracing AI-assisted tooling to accelerate delivery and improve data quality, while maintaining strong working knowledge of existing data tooling to support and maintain legacy data integrations and solutions.
Primary Duties and Responsibilities
I design, build, support and maintain scalable, secure data pipelines and integrations across the organisation's data estate.
I develop and maintain data models, ETL/ELT pipelines and analytics solutions using Azure Synapse Analytics, Snowflake, Power BI and related data tooling.
I take accountability for the quality, performance and ongoing support of the data solutions I deliver, including legacy data integrations.
I champion effective and responsible use of AI-assisted tooling (e.g. GitHub Copilot, Claude) to improve the speed, quality and efficiency of data engineering delivery.
I work closely with the Development, Cloud and Security engineering teams to ensure data solutions are architected, delivered and operated securely and reliably.
I troubleshoot and resolve complex data issues, including data quality, performance and integration failures, across both modern and legacy platforms.
I maintain and support existing legacy data integrations and solutions, ensuring continuity of service while planning their modernisation where appropriate.
I build and maintain dashboards, reports and self-service analytics capability in Power BI for business stakeholders.
I liaise with business stakeholders to understand data and reporting requirements and translate them into effective technical solutions.
I adopt a security-first approach to the data solutions I design and build, ensuring data is handled in line with governance, privacy and compliance requirements.
I contribute to the definition and evolution of data architecture, standards and best practice across the organisation.
I can accurately estimate the time and effort required for data engineering tasks and projects.
I partner with the Cloud and Development teams to ensure data platforms scale effectively within our cloud infrastructure.
The employee agrees to take on additional reasonable tasks that align with their abilities, if required.
Experience and Educational Requirements
Bachelor's degree in Computer Science, Data Engineering, Information Systems or a related field, or equivalent professional experience.
5+ years of experience in data engineering, data warehousing or business intelligence roles.
Strong hands-on experience with Snowflake or an equivalent cloud data warehouse platform.
Strong hands-on experience with Power BI, including data modelling, DAX and report/dashboard development.
Experience building and maintaining ETL/ELT pipelines and data integrations, including legacy systems.
Practical experience using AI-assisted tooling (e.g. GitHub Copilot, Claude) to improve data engineering delivery.
Strong SQL skills and experience with data modelling, including dimensional modelling and star schemas.
Experience working with cloud platforms (Azure, AWS or GCP) and cloud-native data services.
Understanding of data governance, data quality and data security principles.
Experience working closely with Development, Cloud and Security engineering teams in a cross-functional environment.
Experience with Azure Synapse Analytics is desirable.
GxP, GCP and/or TMF (Trial Master File) knowledge preferred but not mandatory.
Excellent problem-solving skills and the ability to diagnose and resolve complex data issues.
Rapidly absorbs and critically assesses new information and applies it effectively, keeping pace with evolving data and AI tooling.
Strong communication skills, with the ability to translate technical data concepts for non-technical stakeholders.
Makes decisions which impact the success of assigned work, i.e. results, deadlines and quality, and supports collaborative ways of working across the team.
Investigates, defines and resolves complex data issues across a broad range of technical contexts.
Learning and professional development — keeps own data and AI tooling knowledge current and shares learning with the team.
Security, privacy and ethics — fully understands the importance and application to own work and the operation of the organisation.
Minimum Skills, Knowledge and Ability Requirements
Communicates fluently, orally and in writing, and can present complex data concepts to both technical and non-technical audiences.
Confidently evaluates when and how to use AI-assisted data tooling, and champions responsible adoption of AI-assisted tooling across the team.
Strong working knowledge of data tooling and platforms (e.g. Snowflake, Power BI), with the ability to maintain and support existing legacy data integrations and solutions.
Collaborative mindset, working effectively across Development, Cloud and Security teams to deliver secure, reliable data solutions.
Forward-looking approach to technology, keeping up to date with emerging data and AI tooling and identifying opportunities for efficiency gains.
Strong analytical and problem-solving skills, with a s