About Us:
Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Role Summary:
We are looking for a Sr. Staff Platform Architect to join our Data Engineering & Analytics team and help shape the future of our data platform. You will be the strategic technical leader responsible for designing, guiding, and implementing next-generation architecture to scale our pipelines, integrate cutting-edge technologies, and unlock advanced analytics capabilities. You will work closely with data engineers, analysts, and business stakeholders to ensure our platform is robust, performant, and future-ready.

Responsibilities:

• Lead the architectural vision for our data platform, ensuring scalability, reliability, and cost efficiency across AWS, Databricks, and MongoDB.
• Partner with engineering leadership to define and implement technical roadmaps for data ingestion, processing, storage, and analytics.
• Evaluate and introduce emerging technologies (e.g., real-time processing, ML feature stores, geospatial analytics) to enhance platform capabilities.
• Guide the design and implementation of large-scale, high-performance data pipelines supporting both batch and streaming workloads.
• Establish and enforce best practices for data modeling, governance, security, and performance optimization.
• Collaborate with analytics teams to enable self-service BI, advanced analytics, and AI/ML experimentation at scale.
• Serve as a technical mentor for senior engineers, fostering a culture of innovation and continuous improvement.
• Ensure architecture aligns with compliance, privacy, and data protection requirements.

Qualifications:

• 12+ years of experience in data engineering, platform architecture, or related technical leadership roles.
• Proven experience designing large-scale, cloud-native data platforms (AWS preferred).
• Deep expertise in Databricks (Delta Lake, DLT, Spark optimization, Databricks SQL) and MongoDB.
• Strong understanding of streaming and batch data processing architectures.
• Experience with advanced analytics enablement, including integration with BI tools, feature stores, and ML platforms.
• Strong knowledge of data governance, privacy, and security best practices.
• Hands-on coding skills in Python, Scala, or Java for prototyping and proof-of-concepts.
• Excellent communication and stakeholder management skills.
• Self-starter who works independently and thrives in an ambiguous, fast-paced Environment.

Nice to Have

• Experience with geospatial data processing and visualization.
• Familiarity with tools like Hex, Streamlit, and modern data catalog/lineage platforms.
• Prior experience in automotive, IoT, or large-scale sensor data domains.

Pay Disclosure:
Salary Range for California Based Applicants: $265,000.00 - $331,300.00 (actual compensation will be determined based on experience, location, and other factors permitted by law).
Benefits Summary: Rivian provides robust medical/Rx, dental and vision insurance packages for full-time employees, their spouse or domestic partner, and children up to age 26. Coverage is effective on the first day of employment.
Company Statements:

• Lead the architectural vision for our data platform, ensuring scalability, reliability, and cost efficiency across AWS, Databricks, and MongoDB.
• Partner with engineering leadership to define and implement technical roadmaps for data ingestion, processing, storage, and analytics.
• Evaluate and introduce emerging technologies (e.g., real-time processing, ML feature stores, geospatial analytics) to enhance platform capabilities.
• Guide the design and implementation of large-scale, high-performance data pipelines supporting both batch and streaming workloads.
• Establish and enforce best practices for data modeling, governance, security, and performance optimization.
• Collaborate with analytics teams to enable self-service BI, advanced analytics, and AI/ML experimentation at scale.
• Serve as a technical mentor for senior engineers, fostering a culture of innovation and continuous improvement.
• Ensure architecture aligns with compliance, privacy, and data protection requirements