Principal Software Engineer (Data Platform)

• Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy
• We are hiring a Principal Software Engineer to join our data platform (AAP) team in Dublin. The AAP team owns the foundational data infrastructure that powers Toast’s analytics products and AI/ML capabilities: real-time streaming pipelines, a cloud-native data lakehouse, feature serving for ML-driven product experiences, and the infrastructure that enables product teams across Toast to build intelligent, data-driven experiences for our 170,000+ restaurant customers
• We are in the middle of a significant platform evolution: migrating to Apache Iceberg, standing up a new Feature Store, and scaling our streaming infrastructure to meet the demands of a rapidly growing business
• As a Principal Software Engineer, you’ll contribute to the technical strategy for our most critical data platform initiatives - deep hands-on work with Spark and Iceberg, driving architectural decisions grounded in how these technologies actually behave under load, and helping shape the platform’s touch points with the same care you’d bring to an external product
• You’ll work closely with other senior engineers and technical leads, influence adjacent teams, and mentor engineers across the organisation - articulating technical direction clearly to engineering, product, and leadership, and bringing people along through a significant platform transformation. Success looks like other engineering teams moving faster because of the platform you help build
• Work hands-on with Spark, Iceberg, and our streaming infrastructure - diagnosing performance, reasoning through architectural decisions, and building systems that other teams depend on at scale
• Contribute to technical strategy for data platform initiatives alongside other senior engineers and technical leads, translating complex problems into clear direction and executable plans
• Design and evolve the platform’s API surfaces so that engineers across Toast can self-service - adoption and ease-of-use are part of the job
• Influence adjacent teams and align stakeholders across engineering, product, and leadership on architectural decisions
• Mentor engineers on the team and raise the bar on engineering practices across the organisation
• Use AI tooling as a genuine force multiplier in your day-to-day work and help the team do the same
• Our data platform runs on AWS and spans Apache Iceberg for table format and lakehouse architecture, Apache Kafka and Pulsar for real-time streaming, Apache Spark for data processing, and DynamoDB and Postgres for operational data stores. We are migrating from legacy ETL patterns toward a modern, cloud-native data lakehouse and building out Feature Store capabilities to power ML-driven product experiences. Our backend services are primarily Kotlin and Java

Benefits

• Peer and company recognition programs
• Unlimited Vacation
• Sabbatical opportunity after five years
• Professional Development Reimbursement Program
• Commitment to Employee Wellness through resources such as a quarterly Wellness Stipend
• Various peer and company recognition programs
• 401(k) and matching
• Medical, Dental, & Vision Coverage
• Subsidized backup childcare
• Mental Health Benefits- Strong background in streaming infrastructure (Apache Kafka, Apache Pulsar, or similar) and cloud-native data platforms on AWS
• Deep expertise in Apache Spark and Apache Iceberg, not just operational familiarity
• 8+ years in software engineering with meaningful experience in data platform or distributed systems
• Demonstrated ability to drive technical alignment across multi-team environments, including the communication work that makes architectural changes actually stick
• Databricks experience is a bonus but we care more that you understand what’s running underneath it
• Experience designing internal platforms and developer-facing abstractions - you think about your platform’s users as carefully as product engineers think about end users