POSITION IS HYBRID / 3 - 4 DAYS PER WEEK IN THE OFFICE*** Architect and optimize data access layers across heterogeneous storage systems — including relational databases (PostgreSQL, Cloud SQL), columnar warehouses (BigQuery), in-memory caches (Redis), and wide-column stores (Bigtable) — selecting the appropriate store for each access pattern Collaborate with data engineers and analysts to design stored procedures, views, and query patterns in analytical databases that meet strict latency and throughput SLAs for reporting endpoints Implement data aggregation, transformation, and enrichment logic — including time-series rollups, geo-spatial calculations, and unit/timezone conversions — to produce accurate, consistent reporting outputs Build and enforce data contracts and schema evolution strategies to ensure backward compatibility and stability across upstream producers and downstream API consumers Integrate backend services with cloud-native infrastructure (GCP, AWS, or Azure) including event-driven architectures, scheduled jobs, serverless functions, and container orchestration platforms (Kubernetes/GKE) Instrument services with observability tooling — structured logging, distributed tracing, and metrics — and participate in on-call rotations to maintain high availability and reliability targets (SLO/SLA) Apply security best practices including authorization scoping (e.g., segment- or fleet-scoped data access), secrets management, and data privacy controls in compliance with automotive and enterprise data regulations Partner with product, data science, and platform teams in an agile delivery model — contributing to technical design reviews, code reviews, and architectural decisions for new capabilities on the telematics platform. Languages: Kotlin, Java, Python, or equivalent JVM/backend language Frameworks: Spring Boot, gRPC, REST API design Data: BigQuery, PostgreSQL, Redis, Bigtable, Kafka or Pub/Sub Infrastructure: GCP (or equivalent), Docker, Kubernetes, CI/CD pipelines Practices: TDD, MLOps-adjacent data pipeline patterns, database performance tuning, API versioning.