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PwC

Cloud Data Modelling Engineer

PwC is hiring a Cloud Data Modelling Engineer in Warsaw, Poland. Level rates it ; you can apply on PwC.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • The posting allows some remote work.
  • Tools and skills the posting cites include Databricks, Snowflake and Microsoft Fabric.
  • Level classifies it as a senior role.
  • Level lists 3,700+ other open roles at PwC.

AI in this role

Design and develop enterprise cloud data models and architectures using modern transformation tools and frameworks.

DatabricksSnowflakeMicrosoft FabricAzure
data-modellingdatabase-designmaster-data-managementdata-engineering

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).


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.

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 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,
  • And when you start enjoying PwC as much as we do, you may recommend your friend to work with us.


Recruitment process:

  • Apply,
  • Talk to our recruiter on a short HR screening call,
  • Get to know us better during the interviews (technical interview and cultural fit interview).

Send your application today! In case you have any additional questions, contact us: pl_ITrecruitment@pwc.com.

Your personal data will be processed for recruitment purposes by PwC Advisory spółka z ograniczoną odpowiedzialnością sp.k. or another PwC entity which runs a recruitment process - (list of entities). If you have given separate consent, data will also be processed for other purposes in accordance with the content of the consents granted. Full information about processing your personal data is available in the Privacy Policy.

#LI-hybrid #LI-MA1

How we rate this

Cloud Data Modelling Engineer at PwC rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data ModellingDatabase DesignMaster Data ManagementData EngineeringDatabricksSnowflakeMicrosoft FabricAzure

Questions you could be asked

  1. Tell me about a project where data modelling was part of your work. What did you do?
  2. Tell me about a project where database design was part of your work. What did you do?
  3. Tell me about a project where master data management was part of your work. What did you do?
  4. Tell me about a project where data engineering was part of your work. What did you do?
  5. Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Data Modelling, Database Design, Master Data Management, Data Engineering, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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