Senior Data & AI Platform Engineer
Role details
Job location
Tech stack
Job description
job summary: Randstad is seeking a Senior Data & AI Platform Engineer for an onsite role in Washington, DC, supporting a premier national transportation leader. This pivotal role is designed for a technical visionary who will architect and scale a unified, self-service data ecosystem using a modern Databricks lakehouse architecture. You will bridge the gap between complex data engineering and advanced AI, leading the design of automated pipelines, MLOps frameworks, and API-first integrations while mentoring a talented team of engineers. This is a unique opportunity to modernize critical infrastructure and drive data-driven innovation for an organization that connects communities across America.
location: Washington, Washington, D.C. job type: Contract salary: $60 - 65 per hour work hours: 9am to 5pm education: Bachelors
responsibilities: Architectural Leadership: Lead the evolution of a scalable Data & AI platform, integrating Databricks, SAP (Datasphere/S/4), and Denodo virtualization into a governed, self-service ecosystem.
Solution Delivery: Act as a hands-on lead developer for complex data pipelines, feature stores, and API-driven integrations that power enterprise-wide analytics and digital experiences.
MLOps & Automation: Design and implement production-grade MLOps pipelines, including versioning, CI/CD, and monitoring to accelerate the deployment of intelligent models.
Engineering Excellence: Establish and enforce standards for ingestion, transformation, and "governance-as-code" controls embedded directly into technical workflows.
Mentorship: Foster a culture of excellence by providing technical guidance, code reviews, and professional development for junior and mid-level engineers.
Strategic Collaboration: Partner with architects, product owners, and governance leads to align technical solutions with the broader enterprise data roadmap.
qualifications: Education: Bachelor's degree in Computer Science, Data Engineering, or a related technical field (equivalent experience considered).
Experience: 4-6 years of deep technical experience in data engineering, software development, or data architecture.
Technical Proficiency: Advanced expertise in Python and SQL with significant experience in Apache Spark and modern Lakehouse architectures (Databricks preferred).
AI/ML Expertise: Proven experience building MLOps pipelines and internal platform services such as feature stores or semantic layers.
Modern Infrastructure: Strong understanding of API-first and event-driven architectures, secure service-to-service communication, and RBAC security.
Agile Leadership: Demonstrated ability to lead multi-functional teams through technical challenges within a scaled Agile environment.
Soft Skills: Exceptional communication and problem-solving abilities, with the capacity to explain complex technical concepts to diverse stakeholders.
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.
At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.
Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).
This posting is open for thirty (30) days.
,
Architectural Leadership: Lead the evolution of a scalable Data & AI platform, integrating Databricks, SAP (Datasphere/S/4), and Denodo virtualization into a governed, self-service ecosystem.
Solution Delivery: Act as a hands-on lead developer for complex data pipelines, feature stores, and API-driven integrations that power enterprise-wide analytics and digital experiences.
MLOps & Automation: Design and implement production-grade MLOps pipelines, including versioning, CI/CD, and monitoring to accelerate the deployment of intelligent models.
Engineering Excellence: Establish and enforce standards for ingestion, transformation, and "governance-as-code" controls embedded directly into technical workflows.
Mentorship: Foster a culture of excellence by providing technical guidance, code reviews, and professional development for junior and mid-level engineers.
Strategic Collaboration: Partner with architects, product owners, and governance leads to align technical solutions with the broader enterprise data roadmap.
Requirements
Education: Bachelor's degree in Computer Science, Data Engineering, or a related technical field (equivalent experience considered). Experience: 4-6 years of deep technical experience in data engineering, software development, or data architecture. Technical Proficiency: Advanced expertise in Python and SQL with significant experience in Apache Spark and modern Lakehouse architectures (Databricks preferred). AI/ML Expertise: Proven experience building MLOps pipelines and internal platform services such as feature stores or semantic layers. Modern Infrastructure: Strong understanding of API-first and event-driven architectures, secure service-to-service communication, and RBAC security. Agile Leadership: Demonstrated ability to lead multi-functional teams through technical challenges within a scaled Agile environment. Soft Skills: Exceptional communication and problem-solving abilities, with the capacity to explain complex technical concepts to diverse stakeholders.
