PwC Polska

Cloud data engineer

In short

This is a senior Cloud Data Engineer role at PwC Poland's Cloud & Digital team, building data platforms (data warehouses, data lakes) using Azure Databricks, MS Fabric, and Azure Data Factory, and supporting clients' data architecture and governance needs. It requires at least 3 years of data engineering experience, hands-on work with tools like Databricks, Snowflake, BigQuery, Python/PySpark and SQL, plus CI/CD experience with Azure DevOps or Jira. The role is hybrid, based in Warsaw, and involves liaising with senior client stakeholders on data strategy and data quality.

About the Team
As a global leader in cloud services, PwC is supported by PwC Poland's Cloud & Digital team. We provide first-class services in all areas of Cloud Computing, Cloud Strategy, Cloud Migrations, Data Analytics, and DevOps, just to name a few of our core capabilities. We support clients in the transition to and their adoption of cloud infrastructure, creation of new business models and streamlining their operational activities.
Responsibilities
•Building data platforms with critical components including data warehouses and data lakes using tools like Azure Databricks, MS Fabric, and Azure Data Factory for extraction, transformation and loading
•Defining the flow of data through the data platform from the point of ingestion to the point of presentation at the semantic layer using medallion architecture
•Designing the migration plans for moving transactional and master data from legacy systems of record to systems of reference, i.e., new solutions
•Conducting comprehensive data assessments alongside Data Modelers and Analysts across multiple systems of record and data domains to identify and remediate data quality issues
•Liaising with client senior stakeholders and supporting Senior Data Architects to gather functional requirements to design modern data architecture
•Supporting Data Governance subject matter experts to define data standards and policies, specifically around Master Data Management and Data Quality
Requirements
•Minimum of 3 years in data engineering roles, although this can be considered alongside other relevant experience e.g., Business Intelligence, Data Science etc.
•Hands-on experience of using data transformation tools e.g., Databricks, Snowflake, BigQuery, MS Fabric etc.
•Experience in building data warehouses, data lakes and data lakehouses using tools like Azure Data Factory and Azure Synapse Analytics
•Familiarity with writing data transformation scripts using Python (i.e. PySpark) and SQL to query databases
•Some experience in Data Engineering CI/CD practices and release management across Dev, QA and Production environments using tools like Azure DevOps, and/or Jira
•Proficiency in Business English at B2 level or above, with confidence to write technical documentation e.g., designing documents with support from Project Manager
•Experience with new technologies and AI-based tools demonstrated in your daily work (e.g., task automation, information analysis, content creation)
•Some familiarization with Data Science and Data Analytics use cases within the context of Consumer Goods, Retail, Manufacturing and/or Financial Service sectors will stand out
Nice to Have
•Cloud certifications in Azure, AWS, or Google Cloud
•Data Governance certifications e.g., DAMA
•Evidence of training using online platforms e.g. Coursera, Udemy, Datacamp etc.
•Application of data modelling frameworks including Kimball dimensional modelling to design and build logical and physical data models
•Interest and some experience of experimenting with the application of Agentic AI to automate the extraction, transformation and loading of data using services like Azure Foundry
•Proven experience in conducting data assessments across multiple data domains, including Product, and Customer and systems of record e.g. ERPs and CRMs
•Experience of working on Data Strategy and Governance projects with a focus on improving Data Quality across key business functions
•Familiarity with agile project management methodologies like Scrum to enable and scale minimal viable products
•Some exposure to Data Science and Data Analytics use cases, particularly in the applications of Machine Learning and Generative AI techniques to help improve business forecasting and demand planning
•Experience in supporting senior stakeholders including Chief Data Officers in medium to large sized businesses across sectors such as Manufacturing, Consumer Goods, and/or Financial Services
Conditions / Benefits
•Work flexibility - hybrid working model, flexible start of the day, workation, sabbatical leave
•Development and upskilling - full support during onboarding process, mentoring from experienced colleagues, training sessions, workshops, certification co-financed by PwC and conversations with a native speaker
•Wide medical and wellbeing program - medical care package (incl. freedom of treatment, physiotherapy, discounts on dental care), coaching, mindfulness, psychological support, education through dedicated webinars and workshops, financial and legal counseling
•Possibility to create your individual benefits package (a.o. lunch pass, concierge, veterinary package for a pet, massages) and access to a cafeteria - vouchers, discounts on IT equipment and car purchase
•3 paid hours for volunteering per month
•Additional paid Birthday Day off
•Employee referral program

Stop applying.
Get referred.

$10 in free credits

In just 60 seconds, fully on autopilot — Eraldt's AI agents read your CV, map the roles you fit, find live vacancies and the people who can refer you, write personal emails, and get you referred.

This isn't an application: your CV doesn't go to the company, and we don't promise a referral for this exact role.

Discover who else lands interviews on autopilot