Top Scala Jobs in San Diego, CA

The Senior Quality Engineer will enhance the automation framework, improve automated coverage, drive quality in compliance-critical software, and establish testing pipelines while collaborating with multiple teams.

Design, build, and operate scalable, secure data platform infrastructure for ingesting, processing, cataloging, and accessing petabytes of data. Improve Spark/Databricks reliability and developer experience, build ingestion/replication systems, develop internal libraries and tooling (Go/Python), and collaborate with cross-functional teams to support analytics, ML, and customer-facing data products.

Design and develop backend services and APIs for identity resolution, optimize event-driven systems, and enhance system reliability. Mentor engineers and influence architectural decisions.

As a Staff Software Engineer, you'll design and operate traffic infrastructure, lead multi-team projects, ensure service reliability, and mentor engineers while utilizing AI tools for development efficiency.

Design and develop software solutions enhancing user experience for Governance features, contribute to open-source software, communicate technical designs, and support team quality through reviews.

Develop and manage high-performance back-end systems, design secure APIs, optimize performance in cloud environments, conduct testing, and manage ML model lifecycles.

The Sr. Database Administrator will manage SQL Server databases, perform optimization and troubleshooting, and develop data pipelines using Databricks, focusing on enterprise data platforms.

As a Fullstack Engineer, you'll design, build, and operate web applications, collaborating with product teams and mentoring peers while ensuring best practices in coding and system architecture.

The Senior Backend Engineer will develop the Payroll product, overseeing the entire development cycle from design to deployment, in a microservices architecture.

The Java - Scala Architect will need to program in Java and Scala, manage Apache Spark technologies, and work with NoSQL systems. Additional experience with Hadoop, web services, and data pipeline building is preferred.

The Data Engineer designs and builds data pipelines for analytics, ensuring data quality, governance, and integration across systems, while collaborating with teams for effective delivery.

Lead design and implementation of health data products, mentor engineers, own multiple projects, and develop scalable data solutions using modern technologies.

Lead design and implementation of products, mentor engineers, drive innovation, and build scalable data solutions using modern tech stack.

The role involves designing, building, and optimizing a data platform, collaborating with cross-functional teams, and ensuring data quality and security.

Remote backend engineer role building web services and data pipelines using Scala and Java. Requires Akka/Pekko (streams, actors, clustering, persistence, HTTP), functional programming with Cats/Cats Effect, streaming/distributed system design, AWS services (Kinesis, DynamoDB, SQS/SNS, API Gateway, IAM, KMS), SQL optimization, CI/CD, and hands-on high-availability architecture experience.

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.

Build and ship complex consumer-facing full stack applications. Work on React/TypeScript frontends (offline PWAs using IndexedDB/DexieJS and Workbox) and Scala/Play backends with PostgreSQL. Deploy on AWS via Kubernetes. Mentor engineers, collaborate in product-focused cycles, and thrive in a fast-moving startup environment.

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.

Lead platform strategy, architecture, and hands-on development. Design, build, deploy, and operate high-performance, fault-tolerant integrations and platform enhancements. Drive security/compliance, mentor engineers, recruit senior talent, align technology with business goals, and communicate technical vision to stakeholders.

Design, develop, optimize, and deploy high-performance data processing applications using Scala and Apache Spark on Cloudera CDH. Build and tune ETL pipelines integrating HDFS, Hive, Impala, HBase, and Kafka. Ensure data integrity and security, troubleshoot performance, collaborate with data scientists and analysts, and implement version control and CI/CD.

Design, develop, test, optimize, and deploy large-scale Spark/Scala data processing and ETL pipelines on Cloudera Hadoop. Collaborate with data scientists and analysts, ensure data integrity and security, troubleshoot performance, and implement version control and CI/CD for Spark applications.

Design, develop, optimize, and deploy large-scale data processing applications using Scala and Apache Spark within the Cloudera Hadoop ecosystem. Build ETL pipelines, ensure data integrity and performance, troubleshoot Spark/Cloudera issues, collaborate with data scientists and analysts, and implement version control and CI/CD for Spark applications.

Design, develop, optimize, test, and deploy large-scale Spark/Scala data processing and ETL pipelines within the Cloudera ecosystem. Collaborate with data scientists and analysts, ensure data integrity and security, troubleshoot performance issues, and implement version control and CI/CD for production data solutions.

Design, develop, optimize, and deploy high-performance Spark/Scala data processing applications and ETL pipelines within the Cloudera Hadoop ecosystem. Collaborate with data scientists and analysts, ensure data integrity and performance, troubleshoot Spark/Cloudera issues, and implement version control and CI/CD for Spark applications.

Guide customers through cloud data engineering transformations, providing leadership for data projects and architecting production workloads. Collaborate with architects, deliver training, and enhance community adoption using Databricks Intelligence Platform.