Senior Data Engineer

Geolava is a company focused on bringing AI to the physical world through spatial intelligence systems. They are seeking a Senior Data Engineer to build and scale the database infrastructure that powers their products and AI research, involving the design and implementation of secure data pipelines and storage systems.

Responsibilities:

• Drive the technical direction for database solutions used across Product and Research
• Design and implement database solutions that scale to support millions of users across Claude's product ecosystem
• Build and scale database systems through 100x+ growth while maintaining reliability and performance
• Architect data storage solutions that work seamlessly across GCP, AWS, first-party deployments, third-party deployments, and other environments
• Develop database infrastructure that serves both product and research workloads with different performance characteristics
• Partner with product and research teams to understand data requirements and build infrastructure that accelerates innovation
• Work collaboratively with Platform, infrastructure, application engineers, and AI Researchers to build next-generation data platform products and services
• Optimize database performance, reliability, and cost efficiency at massive scale
• Build scalable data pipelines for sourcing, transforming, and publishing data assets for AI use cases
• Ship high-quality, well-tested, secure, and maintainable code
• Navigate roadblocks and deliver solutions quickly and iteratively
• Thrive in a fast-paced, design-driven, product development cycle

Requirements:

• 5+ years of experience (excluding internships/co-ops) in data engineering, building distributed systems and scaling data-intensive systems
• Expertise in distributed database architectures at scale
• Experience at a high-growth company building platform infrastructure relied upon by other teams
• Ability to balance startup speed with production reliability
• Strong technical leadership and cross-functional collaboration skills
• Passion for building data layers that enable next-generation AI
• Extensive experience with Python and PySpark (or Spark)
• Deep expertise in scaling relational and non-relational databases (AWS: Aurora, RDS, DynamoDB, PostgreSQL; GIS experience is a plus)
• Experience with vector databases and async job processing frameworks
• Knowledge of database orchestration and automation at scale
• Experience with security and compliance (ITGC, GDPR, financial controls)
• Background in data warehousing, ETL/ELT pipelines, and analytics infrastructure for ML pipelines
• Proven track record improving data reliability, availability, or cost efficiency
• Security engineering experience focused on data protection and access control