ETIC, Data Engineer, Associate

Advisory

Technology

Advisory - Other

Associate

You’ll be joining our Data engineering, Reporting and Analytics practice, a core part of our Technology, Data & Analytics business unit. We support our clients in delivering a variety of transformation projects across the commercial sector from defining data strategies to helping architect, design and implement modern data and analytics solutions using the latest cloud technologies.
The role will provide you with an opportunity to work across a portfolio of clients, with a focus on large and complex organisations.
You will work in the team that reports to the Data Analytics delivery service leadership team and will be an integral part of the team based in Cairo, as well as those delivering client transformation programmes across the PwC Global Network, including the UK, Germany and Middle East.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Essential skills and attributes:

● 1-3 years hands-on experience of Azure Data Factory, Data Lake Storage, Files, Blob, Synapse, Data Lake Analytics, Event Hub, Data Catalog, Stream Analytics.

● You’ll have +1 years of hands-on experience of data analytics solutions on cloud platforms
● Well versed in data architecture approaches to ingest, model and serve data from various sources including structured and unstructured data sources.
● Comfortable in implementing the right solution, whether that is ELT or ETL.
● Experience in the delivery of solutions through the full lifecycle of a enterprise data platform implementation, including data warehouses, Big Data, MDM and DQM / data profiling
● Modern data lakes and data warehouse solutions.
● Data modelling - the ability to design and implement data models from conceptual through to physical which could include slowly changing dimensions or single customer views
● Dimensional Modelling
● Experience in infrastructure elements of a cloud platform including the setup and implementation of DevOps, networking and security elements.
● Having experience within at least one business area function (e.g Marketing, Sales, Finance, Workforce, Procurement etc.)
● Experience in adapting your communication style to help translate complex technical information to audiences unfamiliar with the technologies.
● Foundational understanding of Data & Analytics architectures, definition of KPIs / metrics and insight requirements
● You should have foundational delivery knowledge in at least one of the following vendors: SAP Business Analytics, Oracle, Cognos, Informatica, IICS, SSIS, Datastage, Talend, data warehouse and data management vendors
● Experience in SQL and performance tuning of queries, ensuring solutions are both scalable and maintainable
● Some practical knowledge of core data modelling, manipulation and visualization skills- for example using tools such as Excel, Alteryx, Power BI / Tableau / Qlik

 

Additional Skills:

● Preferably experience in implementing data visualization using Power BI but will consider other visualization tools.
● Data modelling techniques in Data Vault, Industrial 3NF data Models ex: Accord, TDW, CLDM, etc..

 

Education

● University Degree, in computer science/engineering, business analytics, information systems, or other related disciplines
● Open Group Certified Technical Specialist - Data Engineering is a plus
● Alteryx Certification is a plus
● Microsoft Power BI, Tableau Certification is a plus

● Microsoft Azure Data Engineering Certification is a plus
● Microsoft Azure Fundamentals Certification is a plus

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, AI Fluency, AI-Human Collaboration, Amazon Web Services (AWS), Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 25 more}

Not Specified

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