Cloud Data Architect

PwC Poland’s Cloud & Digital team provides services in cloud computing including Cloud Strategy, Cloud Migrations, Data Analytics, DevOps, Application Modernisation & Cloud Native. They support clients in adopting innovation, creating new business models, and improving business performance across sectors such as Consumer Goods, Retail, Manufacturing, and Financial Services.

• Minimum 5 years in data architecture and data engineering roles or relevant experience such as Business Intelligence or Data Science.
• Hands-on experience with data transformation tools such as Databricks, Snowflake, BigQuery, and Azure Fabric.
• Experience 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, including writing technical documentation.
• Experience with new technologies and AI-based tools for task automation, information analysis, and content creation.

Nice to have:

• Cloud certifications in Azure, AWS, or Google Cloud.
• Data Governance certifications such as DAMA.
• Evidence of training through online platforms (e.g., Coursera, Udemy, Datacamp).
• Familiarity with data transformation scripting using Python (PySpark) and SQL.
• Experience with CI/CD and release management using Azure DevOps and/or Jira.
• Knowledge of Kimball dimensional modelling.
• Experience conducting data assessments across multiple data domains and systems.
• Experience with Data Strategy and Governance focusing on Data Quality.
• Familiarity with agile project management methodologies like Scrum.
• Exposure to Data Science and Analytics use cases, especially Machine Learning and Generative AI.
• Experience supporting senior stakeholders like Chief Data Officers in sectors such as Manufacturing, Consumer Goods, and Financial Services.

• Oversee creation of data models to deliver the intended business architecture.
• Create data entity diagrams and data workflows based on inventories of data assets.
• Define data flow through the data platform from ingestion to presentation.
• Design migration plans from legacy systems to new solutions.
• Design and help build modern data architecture for enterprise data platforms.
• Conduct comprehensive data assessments to identify and remediate data quality issues.
• Interface with senior stakeholders leveraging expertise in Databricks, Snowflake, and Azure Fabric to create modern data architecture.
• Act as Technical Lead on data transformation projects supporting data engineers, modellers, and analysts.
• Develop and share perspectives on modern data architecture as part of training efforts.
• Help create data standards and policies, especially around Master Data Management and Data Quality.
• Build data warehouses and data lakes using tools like Azure Data Factory.

Nice to have:

• Writing data transformation scripts using Python (i.e., PySpark) and SQL.
• Experience with Data Engineering CI/CD practices and release management using tools like Azure DevOps and/or Jira.
• Application of data modelling frameworks including Kimball dimensional modelling.
• Experience conducting data assessments across multiple data domains including Product and Customer systems of record (e.g., ERPs and CRMs).
• Working on Data Strategy and Governance projects focusing on improving Data Quality.
• Familiarity with agile methodologies like Scrum to enable and scale minimal viable products.
• Exposure to Data Science and Data Analytics use cases, including Machine Learning and Generative AI techniques.
• Supporting senior stakeholders including Chief Data Officers in medium to large businesses across sectors such as Manufacturing, Consumer Goods, and Financial Services.