Top Senior Level Scala Jobs in Minneapolis, MN

The Senior Software Engineer in the Life Sciences Team will enhance Domino Datasets functionality through API access, improve version control in Domino Projects, design regulatory compliance features, implement audit logging, automate data version tracking, and optimize workspace performance using Kubernetes technology.

The Technical Leader, Software Engineer will build scalable distributed solutions for Cisco Meraki's platform, working closely with engineering teams to ensure system performance and reliability. Responsibilities include managing project direction, optimizing solutions, and collaborating with various teams, all while adhering to agile methodologies.

As the Engineering Team Lead for our Payroll Product, you'll hire and lead a diverse team of Engineers, partnering with Product to build and execute a roadmap. You'll drive technical excellence throughout the development cycle, manage a continuous delivery environment, and foster collaboration across multiple global teams.

As a Senior Staff Software Engineer, you will lead projects within the Online Infrastructure team, shaping Affirm's strategy for computing workload management. Your responsibilities include designing frameworks and tools for secure scalability, mentoring engineers, and collaborating across teams to meet business needs.

The Senior Software Engineer will join the blockchain product team to lead engineering efforts, design and support customer-facing products on distributed ledger technology, provide technical support, and document features and resolutions. Responsibilities include triaging software issues and prioritizing customer requests.

The Scala Developer will design and develop features for a Data Management product, ensuring compliance with guidelines. Responsibilities include troubleshooting customer issues, collaborating with teams, and staying updated on technology advancements.

As a Senior Data Engineer, you will lead the development of scalable data infrastructure and real-time systems to handle large-scale raw data. Responsibilities include building tools for data analysis, improving data quality, implementing CI/CD pipelines for data operations, and addressing data requests while collaborating closely with machine learning engineers and data scientists.