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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

Cloud Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeWarsaw, PolandNo salary listed

About the Job

Requirements

  • Minimum of 3 years in data engineering roles, or relevant experience such as Business Intelligence or Data Science.
  • Hands-on experience using data transformation tools such as Databricks, Snowflake, BigQuery, or Microsoft Fabric.
  • Experience building data warehouses, data lakes, and data lakehouses using tools such as Azure Data Factory and Azure Synapse Analytics.
  • Familiarity with writing data transformation scripts using Python, including PySpark, and SQL to query databases.
  • Some experience in Data Engineering CI/CD practices and release management across development, quality assurance, and production environments using tools such as Azure DevOps and/or Jira.
  • Business English proficiency at B2 level or above, including confidence writing technical documentation such as design documents with support from a Project Manager.
  • Experience with new technologies and AI-based tools demonstrated in daily work, such as task automation, information analysis, or content creation.

Responsibilities

  • Build data platforms with components including data warehouses and data lakes using tools such as Azure Databricks, Microsoft Fabric, and Azure Data Factory for extraction, transformation, and loading.
  • Define data flow through a platform from ingestion to presentation at the semantic layer using medallion architecture.
  • Design migration plans to move transactional and master data from legacy systems of record to new systems of reference.
  • Conduct data assessments with Data Modelers and Analysts across systems of record and data domains to identify and remediate data quality issues.
  • Liaise with senior client stakeholders and support Senior Data Architects in gathering functional requirements to design modern data architecture.
  • Support Data Governance subject matter experts in defining data standards and policies, particularly for Master Data Management and Data Quality.

Desired Qualifications

  • Familiarity with Data Science and Data Analytics use cases in Consumer Goods, Retail, Manufacturing, and/or Financial Services.
  • Cloud certifications in Azure, AWS, or Google Cloud.
  • Data Governance certifications such as DAMA.
  • Training evidence from online platforms such as Coursera, Udemy, or DataCamp.
  • Application of data modelling frameworks, including Kimball dimensional modelling, to design and build logical and physical data models.
  • Interest and some experience experimenting with Agentic AI to automate data extraction, transformation, and loading using services such as Azure Foundry.
  • Experience conducting data assessments across multiple data domains, including Product and Customer, and systems of record such as ERPs and CRMs.
  • Experience working on Data Strategy and Governance projects focused on improving Data Quality across key business functions.
  • Familiarity with agile project management methodologies such as Scrum to enable and scale minimal viable products.
  • Exposure to Data Science and Data Analytics use cases, particularly applying Machine Learning and Generative AI techniques to improve business forecasting and demand planning.
  • Experience supporting senior stakeholders, including Chief Data Officers, in medium to large-sized businesses across Manufacturing, Consumer Goods, and/or Financial Services.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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