Cloud Data Modelling Engineer

Job Description & Summary 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. To get a better insight into the PwC Poland C&D capability please refer to PwC Digital Foundations Hubs as per LINK. We are looking for: Cloud Data Modelling Engineer Your future role: Designing conceptual and logical data models and developing these into physical data models to enable the development and scaling of enterprise data platforms, Building relational, distributed, hierarchical, object-orientated and NoSQL databases and configuring level of granularity, degree of normalization and relationships between data entities therein, Creating data entity diagrams and data workflows across multiple data domains, systems of record and data assets, to meet the functional requirements of end business users from key business functions like Finance, Supply Chain, Marketing etc., Supporting Data Architects to design modern data architecture for enterprise data platforms that rely on harmonized, standardized and enriched data, Working alongside a team of data engineers to extract, load and transfer data from legacy systems of record to systems of reference i.e., reports, applications, dashboards, Conducting comprehensive data assessments across multiple systems to identify and remediate data quality issues relating to master records and transactional data, Developing team expertise in the automation of building physical data models using tools such as Azure Databricks Agentic Bricks, and/or MS Foundry, Fabric and Ontology, Sharing perspectives with the wider team on data modelling techniques and frameworks, e.g., Kimball Dimensional modelling, Developing data standards and policies specifically around Master Data Management and Data Quality. Apply if you have: Minimum of 5 years in cloud data modelling and 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, MS Fabric etc., Experience in conducting data modelling activities with a focus on developing Logical Data Models into Physical Data Models using frameworks like Kimball Dimensional Modelling, Familiarity with writing data transformation scripts using Python i.e. PySpark and SQL to query databases, Proficiency in Business English at B2 level or above, with confidence to write technical documentation e.g., designing documents with support from Project Manager, Proven experience in conducting data assessments across multiple data domains, including Product, and Customer and systems of record e.g. ERPs and CRMs, Experience in building data warehouses, data lakes and data lakehouses using tools like Azure Data Factory and Azure Synapse Analytics, Some familiarity with using Master Data Management tools like Informatica, Stibo, Syndigo, Profisee, CluedIn etc., Experience with new technologies and AI‑based tools demonstrated in your daily work (e.g., task automation, information analysis, content creation).

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. By joining us you gain: Work flexibility - hybrid working model, flexible start of the day, workation, sabbatical leave, Development and upskilling - our full support during onboarding process, mentoring from experienced colleagues, training sessions, workshops, certification co/financed by PwC and conversations with native speaker, Wide medical and wellbeing program - medical