Cloud Data Engineer
PwC is hiring a Cloud Data Engineer in Warsaw, Poland. Level rates it ; you can apply on PwC.
Level's read on this job
- Little AI ●○○○ is how Level rates this data engineer role: aI is not part of the work.
- The posting mentions Databricks, Azure Databricks and Microsoft Fabric among its tools and skills.
- Level classes it as a mid-level role.
- PwC has 3,700+ other open roles on Level.
AI in this role
Cloud Data Engineer building modern data platforms, data lakes, and data warehouses using Azure tools, Databricks, and Python.
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 rate this
Cloud Data Engineer at PwC rates 0 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.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Pay
- Typical data engineer job
- $147k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data warehousing was part of your work. What did you do?
- Tell me about a project where ci/cd was part of your work. What did you do?
- Tell me about a project where data migration was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, ETL, Data Warehousing, CI/CD, and Data Migration. 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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