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PwC

Cloud Data Architect

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

Level's read on this job

  • Level rates this role Little AI ●○○○: aI is not part of the work.
  • The posting mentions Databricks, Snowflake and Azure Fabric among its tools and skills.
  • Level classes it as a senior role.
  • PwC has 3,700+ other open roles on Level.

AI in this role

Design and build modern cloud data architectures and data platforms using enterprise data transformation tools.

DatabricksSnowflakeAzure FabricAzure Data FactoryBigQuery
data-architecturedata-engineeringdata-modelingdata-warehousing

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, such as Cloud Strategy, Cloud Migrations, Data Analytics, DevOps, Application Modernisation & Cloud Native. We support clients in their adoption of innovation, creation of new business models and streamlining their operational activities. We also improve the business performance of organisations.


We are looking for:
Cloud Data Architect


Your future role:

  • Overseeing the creation of data models to enable the delivery of the intended business architecture,
  • Creating data entity diagrams and data workflows according to the inventories of data assets,
  • Defining the flow of data through the data platform from the point of ingestion to the point of presentation,
  • Designing the migration plans for moving data from legacy systems of record to systems of reference i.e., new solutions,
  • Designing and helping to build modern data architecture for enterprise data platforms that rely on harmonized, standardized and enriched data,
  • Conducting comprehensive data assessments across multiple systems of record and data domains to identify and remediate data quality issues,
  • Interfacing senior stakeholders and leveraging expertise in data transformation tools such as Databricks, Snowflake, and Azure Fabric to create modern data architecture,
  • Acting as the Technical Lead on data transformation projects and support a muli-faceted team of data engineers, data modellers and data analysts to help them design and build target state architecture,
  • Developing and sharing perspective on modern data architecture, as part of the training and development effort,
  • Helping the wider Data team to create data standards and policies and specifically around Master Data Management and Data Quality,
  • Building data warehouses and data lakes using tools like Azure Data Factory, and insights into Data Science and Data Analytics use cases within the context of Consumer Goods, Retail, Manufacturing and/or Financial Service sectors will stand out.


Apply if you have:

  • Minimum of 5 years in data architecture 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, BigQuery, Azure Fabric etc.,
  • Experience in building data warehouses, data lakes and data lakehouses using tools like Azure Data Factory and Azure Synapse Analytics,
  • 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).


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.,
  • 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,
  • Application of data modelling frameworks including Kimball dimensional modelling to design and build logical and physical data models,
  • 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.


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.


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 Architect 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 ArchitectureData EngineeringData ModelingData WarehousingDatabricksSnowflakeAzure FabricAzure Data Factory

Questions you could be asked

  1. Tell me about a project where data architecture was part of your work. What did you do?
  2. Tell me about a project where data engineering was part of your work. What did you do?
  3. Tell me about a project where data modeling was part of your work. What did you do?
  4. Tell me about a project where data warehousing 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 Architecture, Data Engineering, Data Modeling, Data Warehousing, 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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