Level

PwC

Cloud Data Engineer

AI in this role

databricks

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 Engineer


Your future role:

  • 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 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 and specifically around Master Data Management and Data Quality,
  • Some familiarizations with 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 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).


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.

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 score this

Cloud Data Engineer at PwC scores 23 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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