Software Engineer - Data team

About Masabi

At Masabi, we’re driving the fare payment revolution, powering the journeys of millions all over the world. We build fare collection platforms that allow riders to seamlessly buy and present tickets for public transport either on their mobile phones, from a ticket machine, or even by tapping their bank card to travel.

Our Justride platform is used in over 250 locations globally, including some of the largest cities in the world. With our industry-first mobile ticketing SDK, we’ve partnered with large players in the transport space, including Uber, Moovit, and Transit.

The Role

We’re building our next data platform. Our ticketing, validation, and payment services already publish events to Kafka, and over the coming year we’re turning those events into a governed lakehouse on AWS that transit agencies, internal teams, and our APIs can query. It will replace our current Elasticsearch-based data store.

You’ll join a small Data team of software engineers who design as well as build: choosing approaches, measuring performance and cost, and documenting choices. You’ll bring software engineering practices to a data platform, from well-tested services and CI checks to infrastructure as code. What you build will shape how agencies and our own teams use their data.

This is a fully remote contract role for candidates based in Poland.

Responsibilities

• Build and run the services that ingest Kafka topics into Apache Iceberg tables on AWS, including partitioning, compaction, deduplication, and backfills of historical data.
• Write clean, well-tested, maintainable code, using AI tools with good judgement, and contribute to code reviews and shared engineering standards.
• Work with data-producing teams on data contracts, including Avro schemas with field-level classification, schema evolution rules, and enforcing CI checks.
• Build privacy and access controls into the platform: personal data erasure, retention, and per-agency access control.
• Build the query layer behind our customer-facing data API, and provide access through Athena.
• Evaluate technical approaches, measure performance and cost, and document trade-offs.
• Migrate existing dashboards, reports, and finance extracts onto the new platform.
• Build the curated layer of shared metrics and business-ready datasets for BI tools and an AI analytics assistant.

What You’ll Need

• Software Engineering Fundamentals: Ability to write production code, test properly, and work comfortably with Git and CI pipelines.
• AI Fluency: Daily use of AI coding tools with careful validation, especially for SQL, schema changes, and data correctness.
• Data Pipelines & SQL: Strong SQL skills and experience building or running data pipelines from source to query.
• Data Modelling: A solid grasp of data modelling principles.
• Communication: Clear, confident written and spoken English.

What Will Help You Thrive

• Experience running a lakehouse or data warehouse in production.
• Production experience with Kafka and schemas (ideally Avro).
• Experience handling personal data, including privacy, retention, and access control.
• Comfort making design decisions and explaining trade-offs in writing and speech.
• Experience collaborating closely with data-producing teams.
• Nice to Have: JVM experience (Kotlin or Java), Apache Iceberg, Terraform, AWS Lake Formation, DuckDB.

What You’ll Learn

• How to build a data platform from the ground up for a global fare payment system.
• Hands-on experience with a modern lakehouse stack: Iceberg, Athena, Lake Formation, Kafka, and Avro on AWS.
• Shaping technical direction in a small team where your design choices set the standard.
• Effective real-world application of AI engineering tools.

Tech Stack

• Languages: Java or Kotlin
• Cloud & Analytics: AWS (S3, Apache Iceberg, Athena, Lake Formation)
• Databases: PostgreSQL, DuckDB
• Messaging & Schemas: Kafka with Avro
• Infrastructure & CI: Terraform, GitLab CI