Top Scala Jobs in San Diego, CA

Design, build, and maintain scalable Azure data pipelines and platforms using Azure Databricks, Synapse, Data Factory, and Microsoft Fabric. Implement IaC (Bicep/ARM/Terraform), CI/CD with Azure DevOps, monitor platform stability, optimize Spark jobs, and collaborate with architects and stakeholders to meet business requirements.

Design and deliver scalable, secure data platforms and architectures (Databricks/cloud) for customers. Split time between billable and pre-sales, lead solution design, mentor teams, ensure data governance and security, validate ETL/data pipelines, produce documentation and presentations, and manage multiple customer accounts to deliver production-ready data solutions.

Lead refactoring and optimization of scalable data pipelines, design next-generation distributed storage and processing systems, build clean interfaces for diverse data consumers, mentor engineers, and establish engineering standards and processes.

Lead architecture and delivery of scalable, resilient distributed web applications and AI/LLM-powered features. Drive technical vision, enforce engineering best practices, mentor engineers, collaborate with product and platform teams, and productionize generative AI capabilities with attention to testing, observability, security, and performance.

Build and maintain full-stack features on a product-oriented team, owning product areas end-to-end. Ship customer-facing functionality, design and optimize data models and schemas, work with React state management, relational databases, cloud services, event streaming, caching, and AI tools. Collaborate cross-functionally, take high ownership, and occasionally support mission-critical work outside normal hours.

Design, develop, and maintain scalable backend services and distributed systems using Scala, Java, and the Akka ecosystem; build RESTful APIs and cloud-native solutions on AWS; design data access with Slick/SQL; maintain CI/CD pipelines; participate in architecture, code reviews, troubleshooting, and performance improvements.

Design and implement automated test frameworks and data validation utilities for enterprise data platforms. Validate data transformations, pipelines, lineage, and performance across Databricks, Snowflake, Spark, Hadoop and cloud environments. Integrate tests into CI/CD, perform white-box and performance testing, investigate production defects, and collaborate with Data Engineering, Analytics, and business stakeholders to ensure P&C insurance data quality and regulatory readiness.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

Design, build, and maintain scalable data pipelines and ingestion agents for fleet robotics. Define efficient data formats/protocols, implement observability and big-data processing (Spark/Kafka), and build cloud tools (S3, Athena, SageMaker) for analytics, IoT integration, and long-horizon forecasting to improve robot performance and operational insights.

As a Founding Engineer, you'll develop disruptive observability products, optimize software stacks, engage with customers, and contribute to company culture.

As a Principal Software Engineer, you will architect AI-enabled systems, mentor teams, and guide technical decisions for scalable products.

The Databricks Architect will design and implement data architecture solutions using Databricks, AWS, and Snowflake, focusing on MLOps and data governance.

Lead end-to-end feature development across frontend and backend for an enterprise data analytics platform. Design, implement, and maintain React UIs, backend services, APIs, databases, and distributed systems. Collaborate with Product, UX, and Engineering, mentor engineers, improve quality through testing/CI, and introduce new technologies including AI-assisted development.

Define and socialize end-to-end architecture for a multi-tenant, cloud-native SaaS data platform. Lead designs for streaming, low-latency query, multi-cloud deployments, security/compliance, SRE practices, and AI/agent integrations while mentoring senior engineers and influencing executive and customer decisions.

The Principal Engineer will architect and develop scalable AI-driven data platforms, mentoring engineers and aligning technical strategies with business goals.

The role requires a Java - Scala Architect to lead data engineering solutions, manage Apache Spark, and work with NoSQL systems while collaborating on data pipelines and processing large datasets.

Lead backend development for MapMyFitness, collaborate with product/marketing/design, build and maintain APIs for mobile clients, respond to bugs, monitor and resolve incidents, ensure high availability, ship maintainable/testable code, and drive major architectural changes for a platform used by millions.

You will design, build, and maintain scalable applications using Java and JavaScript, collaborating across teams and managing databases.

The Senior Backend Engineer will design and build backend systems for a multi-cloud platform, ensuring performance, scalability, and high quality while collaborating with various teams and stakeholders.

Develop and maintain language frontends for the Joern platform for automated software vulnerability analysis, collaborating with a global team.

The Lead Rust Software Engineer will design and build scalable applications, mentor teams on Rust, and contribute to complex product development.

Lead backend architecture and implementation for scalable, reliable cloud-hosted web products. Mentor engineers, set standards, integrate agentic AI coding tools, design systems applying ML to large datasets, and balance customer-facing features with technical debt and performance.

Design, build, and maintain data platform tools, ensuring data quality and integrity. Collaborate with data science teams and enforce best software practices.

Design, build, test, and operate modern web applications and integrations. Develop performant, accessible UIs using Angular/TypeScript, collaborate across product and infra, support cloud-native services, CI/CD, observability, and responsibly use AI-assisted tools to deliver production-ready software.

Own and improve the end-to-end developer experience for AIMS ML teams: local/remote dev environments, build/test infrastructure, CI/CD, and internal platforms. Design, build, and operate large-scale build and CI systems, remove developer friction, instrument workflows, drive adoption, and set technical standards. Partner with ML researchers to prioritize productivity investments and evaluate/integrate GenAI-powered developer tooling with safety guardrails.