Senior Data Engineer – AI, Data & Cloud (Hybrid)

EY; Dallas (TX); On-site; USD 66,000 - 134,000; Full time

Job summary

EY is seeking a Senior Data Engineer to join the Service Delivery Center in the US. You will work with diverse teams to deliver AI and data services, increasing data value for financial services clients and building scalable data platforms in the cloud.

The role emphasizes collaboration, in‑person engagement, and ongoing skills development within EY’s FS O practice. You will collaborate with client teams, mentor peers, and own data movement quality, while applying ETL techniques and SQL across

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience
• At least 3 years of relevant experience in data engineering and cloud data platforms
• Experience with business, management and technology concepts
• Experience with ETL suites and DBMS
• Knowledge of data reporting solutions and data visualization
• Practical experience with SQL Server, MySQL, Oracle or DB2 and SQL syntax
• Willingness to travel up to 30%
• Role is at least 60% in-person engagement to support teaming and delivery

Responsibilities

• Work with diverse teams to deliver AI and data services.
• Be a team player with strong communication and a willingness to learn technical skills.

Skills

Team collaboration

Mentoring

Communication

Accountability

Stakeholder management

Technical depth

ETL coding

Data movement analysis

Education

Bachelor’s degree in CS/Engineering/IS or related

Tools

Informatica

Infosphere

Ab Initio

SAP

Job description

EY is seeking a Senior Data Engineer to join the Service Delivery Center in the US. You will work with diverse teams to deliver AI and data services, increasing data value for financial services clients and building scalable data platforms in the cloud.

The role emphasizes collaboration, in‑person engagement, and ongoing skills development within EY’s FS O practice. You will collaborate with client teams, mentor peers, and own data movement quality, while applying ETL techniques and SQL across