itD is seeking a Data Engineer IV to design, build, and optimize scalable data infrastructure that supports AI infrastructure and inference initiatives for a high-performing engineering organization. The ideal candidate will bring deep expertise in data engineering, AWS, large-scale ETL development, and analytics, with a proven track record of building end-to-end data pipelines and delivering reliable enterprise data solutions.
Responsibilities:
- Design, develop, and maintain end-to-end data pipelines and scalable data architectures using AWS technologies
- Build and optimize ETL processes that transform raw data into structured, analytics-ready datasets
- Design, implement, automate, and support enterprise-scale data management systems that meet business and engineering requirements
- Partner with AI infrastructure engineers, data architects, and cross-functional stakeholders to improve data reliability, scalability, and operational efficiency
- Develop high-performance data processing solutions, prototypes, and proof-of-concept implementations to support infrastructure initiatives
- Manage data engineering projects through the full development lifecycle, from requirements gathering to deployment and ongoing optimization
- Identify opportunities to improve existing data processes, enhance system performance, and implement engineering best practices
- Attend regular internal practice community meetings
- Collaborate with your itD practice team on industry thought leadership
- Complete client case studies and learning material (blogs, media material)
- Build out material to contribute to the Digital Transformation practice
- Attend internal itD networking events (in person and virtual)
- Work with leadership on career fast-track opportunities
Requirements:
- Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, or a related technical field
- 8+ years of experience in data engineering or a related technical discipline
- Experience designing and building end-to-end data pipelines from scratch using AWS
- Experience developing and maintaining large-scale ETL processes and enterprise data solutions
- Experience transforming raw data into structured, analytics-ready data models and tables
- Strong analytical skills with experience solving complex data engineering challenges
- Experience collaborating with data architects, software engineers, and cross-functional technical teams
- Excellent written, verbal, and presentation communication skills
- Experience supporting AI infrastructure, machine learning platforms, or inference systems
- Infrastructure engineering or platform engineering experience
- Previous experience working in large-scale technology organizations
- Previous experience supporting Meta or similar enterprise environments
- Process improvement certifications such as Six Sigma, CBPP, BPM, ISO 20000, ITIL, or CMMI