Data Engineer IV (6249)

itD Tech

2d•Remote

About The Position

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, transforming raw data into production-ready datasets, and delivering reliable enterprise data solutions that improve operational efficiency and system reliability.

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.

Nice To Haves

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.

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.