scala jobs in San Diego

Senior software engineer responsible for designing, developing, and maintaining cloud-based backend systems and data pipelines for medical device software at Dexcom. You'll build distributed systems, APIs, and ETL/ELT pipelines that ingest and transform large-scale data, integrate AI insights, and serve internal systems and external partners.…See more The role requires 5–8 years of experience with general-purpose programming (Java/Kotlin/Scala preferred), cloud platforms (AWS/Azure/GCP), CI/CD, and data platform architecture, with mentorship of junior engineers expected.

Lead the design and development of an enterprise-grade payment hub and cash management platform for a wealth management client, architecting microservices, API-first, and cloud-native solutions. Drive end-to-end technical design including integrations with banking and fintech systems using middleware like PortX, ThoughtMachine, and API management platforms.…See more Provide technical leadership and mentorship to engineering teams, define architecture standards, and ensure security, scalability, and performance benchmarks across payment and treasury workflows.

Lead hands-on modernization of legacy SSIS/SSRS ETL workloads into cloud-native Lakehouse pipelines using Databricks, dbt, Fivetran, and Airflow. Design and enforce standardized data frameworks (ingestion, transformation, curation, consumption), drive CI/CD and observability practices, and mentor engineers on modern data engineering patterns.…See more Evaluate emerging technologies (Delta Live Tables, Iceberg, streaming, AI-driven observability) through POCs and POVs, and leverage AI-assisted tools (Databricks Assistant, GitHub Copilot, Cursor AI) to accelerate development and reduce technical debt. Optimize Spark workloads and orchestration across Azure and GCP environments while partnering with architects, platform engineers, and business stakeholders.

Staff Data Engineer to architect and build fault-tolerant, scalable big-data platforms supporting high-velocity analytics use cases across Intuit. Responsibilities include designing data normalization, lineage, governance, and discoverability systems; collaborating with product and engineering teams on extensible platform design; and enabling analytics and GenAI/ML initiatives.…See more Requires 8+ years in product/web analytics, advanced SQL and big-data technologies (Redshift, Spark, Hive, BigQuery), Python or Java/Scala, and data pipeline orchestration experience. Role includes code reviews, CI/CD process ownership, mentorship, and translating business strategy into data-driven insights.

Lead the modernization of legacy SSIS/SSRS data systems into cloud-native Lakehouse pipelines using Databricks, dbt, Fivetran, and Airflow. Design standardized frameworks for ingestion, transformation, and consumption layers while driving CI/CD, observability, and engineering best practices across Azure and GCP.…See more Evaluate emerging technologies (Delta Live Tables, Iceberg, streaming ingestion) through POCs and POVs, and leverage AI-assisted tools (Databricks Assistant, Cursor AI, GitHub Copilot) to accelerate development and reduce technical debt. Provide technical guidance to the team and translate business requirements into scalable data solutions.

Lead a data engineering team responsible for building scalable data pipelines, trusted datasets, and reusable data products powering analytics, experimentation, and AI across Scribd. This role blends technical leadership with hands-on architecture guidance; you'll establish engineering standards, drive design reviews, mentor engineers, and partner cross-functionally to translate business needs into production-grade data solutions.…See more Requires 10+ years in data engineering or data platforms, 3+ years leading engineering teams, deep expertise in dimensional modeling and scalable data architectures, and strong SQL plus Python/Scala skills. You'll work with modern cloud data platforms like Databricks, Snowflake, and BigQuery, and distributed processing frameworks like Spark.

Senior software engineer focused on building cloud-based backend services and data platforms for medical device systems at Dexcom. Design and develop end-to-end data pipelines supporting large-scale ingestion, transformation, and storage, while building and maintaining APIs that expose data to internal systems, partners, and mobile apps.…See more Collaborate with Data Engineers, AI/ML Engineers, and Platform teams to integrate AI insights into production systems, ensuring high standards for reliability, performance, scalability, and data quality. Lead through code reviews, design mentorship, and technical guidance while contributing to architecture decisions and long-term platform roadmap.

Staff Data Engineer role at Credit Karma building petabyte-scale data infrastructure and streaming platforms on GCP. You will design and operate Kafka-based streaming infrastructure, build cloud-native data pipelines using Dataflow/Beam, Flink, and Spark, and create persistence frameworks across Spanner, MySQL, and BigQuery.…See more The role requires 7+ years backend/data systems experience in JVM languages (Scala/Java), expertise with high-throughput distributed systems, and deep knowledge of streaming platforms, Apache Beam, CDC patterns, encryption, and data governance frameworks. You'll also integrate AI/ML and generative AI technologies including LLMs, RAG, semantic search, and knowledge graphs into the data platform.

Design and architect next-generation ML inference infrastructure for globally distributed, multi-tenant model serving with high availability, scalability, and cost efficiency. Lead the development of low-latency, high-throughput inference systems supporting computer vision and multimodal models (CNNs, segmentation, object detection) using Scala, Java, and Go.…See more Build large-scale distributed systems with reactive frameworks, integrate enterprise feature stores, and extend CI/CD pipelines (GitHub Prow, Pulumi) with automation and policy enforcement. Design advanced observability frameworks, optimize ML algorithms for performance, mentor engineers, and ensure MLOps and compliance standards (GDPR, SOC2) across the platform.

Staff Software Engineer leading the design, architecture, and operations of PlayStation's Real-Time Analytics Platform (RTAP), a large-scale distributed data system handling high-throughput, low-latency analytics and stream processing. The role involves architecting and evolving streaming and analytics platforms using Apache Flink, Spark, ClickHouse, and Druid; integrating batch and streaming workloads via lakehouse architectures; and embedding AI capabilities to automate engineering workflows and improve platform reliability.…See more You will own critical platform capabilities end-to-end from design through production operations, mentor engineers, establish technical standards, and influence cross-functional technical strategy across PlayStation's data infrastructure.

Staff Software Engineer leading design and evolution of PlayStation's Real-Time Analytics Platform (RTAP), a large-scale distributed data system handling high-throughput, low-latency analytics and stream processing. Responsibilities include architecting stream processing pipelines, optimizing data services using Apache Flink, Spark, ClickHouse, and Druid, integrating batch and streaming workloads with lakehouse architectures, and building AI-powered capabilities for platform automation.…See more The role requires deep expertise in distributed systems, real-time analytics, and mentoring engineering teams while establishing technical standards and best practices across the organization.

Staff-level engineer designing and operating large-scale distributed data platforms powering real-time analytics across PlayStation. You will lead the architecture and evolution of the Real-Time Analytics Platform (RTAP), own critical capabilities end-to-end from design through production operations, and mentor engineers.…See more Key responsibilities include building and optimizing distributed services using Apache Flink, Spark Structured Streaming, ClickHouse, and Apache Druid; integrating batch and streaming workloads with lakehouse architectures; and establishing technical standards for distributed systems, stream processing, and data modeling.