Top Scala Jobs in Atlanta, GA

Lead design and implementation of Affirm's Lakehouse Platform using Iceberg, Spark, Snowflake, and cloud storage. Drive platform roadmap, governance, access controls, performance and cost optimization, analytics engineering best practices, observability, and on-call readiness. Partner cross-functionally, mentor engineers, and build scalable, secure, self-service data infrastructure and semantic/agentic data tools.

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

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.

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

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.

Develop and maintain Capital Markets applications across the full SDLC. Create functional and technical specs, design and implement modules, enforce engineering best practices, test and support applications, and identify/resolve system deficiencies. Telecommute up to two days weekly.

Lead two engineering teams owning the WMS platform: people management, predictable sprint delivery, platform enhancements, production reliability, incident leadership, and cross-team alignment with product and peers.

Design and operate large-scale data platforms in the cloud, develop data pipelines, support analytics and machine learning, and mentor junior engineers.

The Senior Software Engineer will build and enhance 15Five's Data Intelligence Platform while collaborating with Data Science and Product Engineering teams.

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.

The Sr. Hadoop Developer/Architect will lead design and development of solutions using big data technologies, manage teams, and ensure successful delivery of projects.

The Staff Machine Learning Engineer will design, train, and deploy NLP models, optimize processes, and mentor engineers. The role demands expertise in model training and productionization.

Lead design and implementation of scalable, secure microservices and distributed systems for the Workday Extend developer platform. Drive architecture, reliability, API contract management, CI/CD, and AI-assisted engineering practices while mentoring engineers and collaborating with product and design to deliver resilient cloud-native solutions.

Build and maintain backend APIs, tools, and integrations for HR/payroll products. Design and operationalize agentic/automation workflows, ensure systems are secure, reliable, and scalable, mentor engineers, participate in cross-team initiatives, and improve platform observability and delivery through CI/CD and verification loops.

As a Staff Software Engineer, you'll design and develop systems to integrate AI in healthcare payment processes, mentor engineers, and optimize workflows.

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

The Staff Software Engineer will design and build scalable backend systems, lead projects, and contribute to enterprise software solutions, focusing on application architecture, API development, and ML techniques.

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.

Design, develop, and maintain high-performance Scala/Java backend services and RESTful APIs. Work with SQL databases, Git, and Maven; support distributed systems; write unit tests; perform requirements analysis, system architecture, and performance optimization; participate in design reviews and system integration. Obtain T4 Public Trust clearance.

Design, build, and scale event-driven, distributed backend systems in Python to extract and enrich metadata at massive scale. Lead architecture, mentor engineers, integrate ML/LLM components, optimize performance, and ensure observability and reliability across AWS-based pipelines.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.