Data Engineer Consultant
Posted 12 Oct 2026
Advertised as “Senior Associate/Manager Data Engineer Consultant (Data Bricks) / Technology Consulting”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5–7 yrs
- Management level
- People management
No salary listed for this role.
CertificationsMaster of Business Administration, AWS Certified Data Engineer Associate, AWS Certified Solutions Architect, AWS Certified Big Data - Specialty, Databricks Certified Data Engineer Associate
At EY, we develop you with future-focused skills and equip you with world-class experiences. We empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams.
We work together across our full spectrum of services and skills powered by technology and AI, so that business, people and the planet can thrive together.
We’re all in, are you?
Join EY and shape your future with confidence.
The opportunity
EY AI & Data is the data and advanced analytics capability within EY Asia-Pacific, with over 500 specialist employees working across multiple industry sectors. You will be part of a dynamic team that implements information-driven strategies, data platforms and advanced data analytics solution systems that help grow, optimize and protect client organizations. We are seeking an experienced Data Engineer Consultant to join our team as a senior individual contributor
responsible for designing, implementing, and optimising robust data infrastructure and pipelines. This role offers the opportunity to work hands-on with cutting-edge AWS and Databricks technologies whilst providing technical guidance to team members and collaborating with stakeholders across the organisation on complex data engineering challenges.
Your key responsibilities
1) Data Architecture & Engineering
- Design and implement enterprise-scale data architectures, including data lakes, warehouses, and real-time streaming platforms.
- Develop and maintain ETL/ELT pipelines that efficiently process large volumes of structured and unstructured data from diverse sources.
- Ensure data quality, governance, and security standards are embedded throughout all data engineering processes.
2) Technical Implementation
- Hands-on development of Databricks notebooks using PySpark, Python, and SQL for ETL automation.
- Create and optimise PySpark scripts for efficient data extraction, transformation, and loading from large datasets.
- Implement custom data manipulation, validation, and error handling solutions to enhance ETL robustness.
3) Technical Guidance
- Provide technical mentorship to junior data engineers and analysts.
- Lead code reviews, establish best practices, and drive adoption of modern data engineering tools and methodologies.
- Collaborate with cross-functional teams including data scientists, analysts, and software engineers to deliver integrated solutions.