Data Engineer (Senior Associate), Technology Consulting

About the role

EY is looking for Data Engineers to design, develop and optimise scalable data solutions across cloud platforms. You will work closely with business and technical stakeholders to build reliable data pipelines, enable data-driven insights and support enterprise data transformation initiatives.

Key responsibilities

• Design, build and maintain scalable data pipelines and ETL/ELT processes across cloud data platforms.
• Develop and optimise data models, transformations and workflows using Python and SQL.
• Collaborate with business, analytics and reporting teams to understand data requirements and deliver effective solutions.
• Translate business requirements into technical specifications and data engineering solutions.
• Ensure data is structured and accessible for analytics, reporting and downstream consumption.
• Monitor, troubleshoot and improve the performance, reliability and scalability of data pipelines and storage.
• Contribute to data quality, governance and engineering best practices.
• Support or lead requirements gathering, stakeholder engagement and process documentation.

Required profile

• Bachelor's or Master's degree in Computer Science, Engineering or a related field.
• Experience in data engineering, data integration, data warehousing or related disciplines.
• Hands-on experience with Azure Synapse Analytics and Azure Data Factory (ADF).
• Experience designing, building and maintaining ETL/ELT pipelines and engaging stakeholders to turn business needs into technical solutions.
• Understanding of data modelling and cloud-based data platforms.
• Strong written and verbal communication skills, able to engage technical and non-technical stakeholders.
• Experience in business analysis, including process documentation and requirements management.

Required skills

• Python and SQL
• Azure Synapse Analytics and Azure Data Factory
• ETL/ELT pipeline development
• Data modelling

Good to have: experience with Databricks, Snowflake and/or Power BI; experience in Microsoft Azure environments; experience supporting or leading enterprise-scale data platform implementations; experience mentoring team members.