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Staff Software Engineer (Data Platform)

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Hybrid

Staff Software Engineer (Data Platform)

Toast

Staff Software Engineer (Data Platform)

Skills

KotlinDynamoDBJavaPostgreSQLKafkaAIAWS

20 hours ago

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Important information


Contract type:

Permanent

Location:

Ireland

Work mode:

Hybrid

Published on:

22 October 2026

What they need


  • We are hiring a Staff 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, conducting Databricks evaluations, and scaling our streaming infrastructure to meet the demands of a rapidly growing business
  • As a Staff Software Engineer, you’ll be the technical lead for major parts of this evolution
  • You’ll design and lead the delivery of platform capabilities that several teams depend on, doing deep hands-on work and making design calls that account for streaming, storage, serving, and the teams consuming them
  • You’ll be the go-to expert in your area of the platform, working with product and engineering partners inside and outside our line of business
  • You’ll make the engineers around you better through mentorship, design reviews, and the example you set
  • Success looks like other engineering teams moving faster because of the platform you help build
  • Lead the delivery of significant data platform capabilities, from early design through production rollout, across the AAP team and the teams that depend on it
  • Work hands-on with Kotlin/Java, Spark, Iceberg, and our streaming infrastructure, diagnosing performance, reasoning through trade-offs, and writing the code that sets the pattern for others
  • Anticipate how requirements will change and design systems that can absorb that change, exploring the problem fully before settling on a solution
  • Evolve the platform’s API surfaces so that engineers across Toast can self-service - adoption and ease-of-use are part of the job
  • Lead efforts that measurably improve platform quality, reliability, and observability for the teams and customers who depend on it
  • Mentor other engineers 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 tech stack:
  • 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- Experience building internal platforms and developer-facing abstractions - you think about your platform’s users as carefully as product engineers think about end users
  • 5+ years in software engineering with a strong focus on data platforms or distributed systems, including technical leadership of projects involving more than one team
  • Experience with streaming infrastructure (Apache Kafka, Apache Pulsar, or similar) and cloud-native data platforms on AWS
  • Databricks experience is a bonus but we care more that you understand what’s running underneath it
  • Proficiency in Java, Kotlin or other object-oriented language
  • Strong hands-on expertise in Apache Spark and Apache Iceberg (or similar)

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