[All remote jobs](https://jobicy.com/jobs.md)[![Masabi logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/f2355465-221.png)](https://jobicy.com/company/masabi.md)[Masabi](https://jobicy.com/company/masabi.md) # Software Engineer – Data team AI Summary Masabi is seeking a contract Software Engineer to help build a governed AWS lakehouse for its global public-transport payments platform. The role focuses on ingesting Kafka events into Apache Iceberg, building data services and APIs, and implementing privacy, retention, and access-control capabilities. The engineer will work in a small data team with substantial input into technical design, performance, cost, and engineering standards. Strong software engineering practices, SQL, data modelling, CI, and production data-pipeline experience are central to the role. This is a fully remote role restricted to candidates based in Romania.[Apply for this job](#job-application)[View company](https://jobicy.com/company/masabi.md)ShareRemote from[Romania](https://jobicy.com/job-region/romania.md)SalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentContractExperienceOpen levelPublished7 Nov 2026Apply before7 Dec 2026Listing views37Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. About Us_ // At [Masabi](https://jobicy.com/company/masabi.md), 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. Your own journey is important to us too. Choosing a role here means joining a network of innovators from all walks of life; a group of passionate individuals who consistently deliver. Here, you’ll find the tools you need to build the career you want. Whether you’re taking the direct route or trying a new path, we’ll support you no matter what. ### The Role_ At Masabi, we’re powering the journeys of millions by making public transport payments simple, accessible and seamless. 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 writing your choices down. 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. ### Location_ This is a fully remote contract role for people based in Romania ### 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 the teams that produce the data on data contracts, including Avro schemas with field-level classification, schema evolution rules and the CI checks that enforce them * Build privacy and access into the platform: personal data erasure, retention and per-agency access control * Build the query layer behind our customer-facing data API, and give others access through Athena * Evaluate technical approaches, measure performance and cost, and document the choices you make * Migrate existing dashboards, reports and finance extracts onto the new platform * Later, build the curated layer of shared metrics and business-ready datasets for BI tools and an AI analytics assistant ### About You_ What you’ll need: * Solid software engineering fundamentals: you write production code, test it properly and work comfortably with Git and CI pipelines * AI fluency: you use AI coding tools daily and check their output carefully, especially for SQL, schema changes and anything that affects data correctness * Good SQL and some experience building or running data pipelines, so you’re comfortable working with data from source to query * A solid grasp of data modelling * Clear, confident communication in 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 * You’re comfortable making design decisions and explaining the trade-offs, in writing as well as in conversation * You enjoy working closely with the teams that produce the data, not just the ones that use it * Nice to have: JVM experience (Kotlin or Java), Apache Iceberg, Terraform, AWS Lake Formation, DuckDB We don’t expect you to tick every box. What matters most is curiosity, a willingness to learn, and the motivation to take ownership of your work. ### What You’ll Learn_ * How to build a data platform from the ground up for a global fare payment platform used by transit agencies and millions of riders * Hands-on experience with a modern lakehouse stack: Iceberg, Athena, Lake Formation, Kafka and Avro on AWS * How to shape technical direction in a small team, where your design choices and write-ups set the standard * How to use AI tools well in real engineering work, in a team that encourages them and cares about getting the results right ### Our Stack_ * Java or Kotlin * AWS: S3, Apache Iceberg, Athena, Lake Formation (and potentially more query engines) * PostgreSQL, DuckDB * Kafka with Avro * Terraform, GitLab CI Careers at Masabi are for people going places – driven by a mission to make transit fair and accessible for all. // We are a network of innovators from all walks of life, passionate about making a difference. At Masabi, we operate with openness and trust, creating an environment where everyone feels empowered to bring their whole, authentic selves to work. Whoever you are, just be yourself. // We welcome applications from underrepresented groups, including disabled and neurodivergent people, and can make adjustments at any stage of the process. You’re also welcome to share your pronouns whenever you feel comfortable. Together, we simplify journeys, remove barriers, and improve daily life for millions. Why Join Masabi? * Driven by Purpose – We believe in journeys made simple. The work isn’t always easy, but the best things never are. * Encouraged to Accelerate – Masabi is going places and our people are in the driving seat. Whether you’re taking the direct route or exploring new paths, we support your journey. * Advancing with Empathy – We put people first and foster a culture of learning, not blame. No matter your cargo, we share the load. We’re already powering journeys – are you ready to join us? Show more [Apply now >](https://jobicy.com/jobs/159520-software-engineer-data-team.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThe position requires production-grade software engineering alongside modern lakehouse, streaming, schema-governance, and privacy expertise. It also calls for independent architectural decisions in a small team and careful trade-off documentation. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$90,000US market range (per year)$75k–$110k0$121.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer compensation was disclosed. The annual period and USD figures are inferred estimates for a mid-to-senior contract data-platform software engineering role; the market range is an AI estimate, not verified salary research. ## Core skills Skills and capabilities most closely associated with this opportunity. [Software engineering](https://jobicy.com/jobs?search_keywords=Software%20engineering.md)[Apache Kafka](https://jobicy.com/jobs?search_keywords=Apache%20Kafka.md)[Apache Iceberg](https://jobicy.com/jobs?search_keywords=Apache%20Iceberg.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Data pipelines](https://jobicy.com/jobs?search_keywords=Data%20pipelines.md)[Data modelling](https://jobicy.com/jobs?search_keywords=Data%20modelling.md)[Avro](https://jobicy.com/jobs?search_keywords=Avro.md)[Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md)[GitLab CI](https://jobicy.com/jobs?search_keywords=GitLab%20CI.md)[Athena](https://jobicy.com/jobs?search_keywords=Athena.md)[AWS Lake Formation](https://jobicy.com/jobs?search_keywords=AWS%20Lake%20Formation.md)[Java](https://jobicy.com/jobs?search_keywords=Java.md)[Kotlin](https://jobicy.com/jobs?search_keywords=Kotlin.md)[Data privacy](https://jobicy.com/jobs?search_keywords=Data%20privacy.md) Sample interview questionsHow would you design a service that ingests Kafka events into Apache Iceberg tables?I would begin by defining event contracts and schema-evolution rules, then build an idempotent ingestion service with durable checkpoints. I would select partitioning based on common query patterns and data volume, implement deduplication using stable event identifiers, and schedule compaction to control small files. I would add observability for lag, failed writes, data-quality checks, cost, and table health. How do you approach schema evolution for Avro events used by multiple producer and consumer teams? I establish compatibility requirements before changes are made and validate them in CI against the schema registry or contract repository. Fields should be added with safe defaults where appropriate, destructive changes should be versioned or phased, and ownership should be clear. I also document field classifications so downstream users understand semantic and privacy constraints. What measures would you take to support personal-data erasure and retention in a lakehouse? I would identify and classify personal data at the schema level, apply retention policies by dataset, and ensure access is governed through least-privilege permissions. For erasure, I would design a traceable deletion workflow that locates affected records, rewrites or deletes data safely in Iceberg, and verifies results through audit logs and tests. The approach must include downstream tables and extracts, not just raw ingestion data. How would you evaluate whether a chosen table partitioning strategy is effective? I would start from expected query predicates, ingestion rates, data cardinality, and retention requirements. After implementation, I would measure query scan volume, latency, file counts, compaction behavior, and storage cost using representative workloads. If metrics show excessive scans or small-file overhead, I would adjust partition transforms or introduce targeted clustering while documenting the trade-offs. How do you use AI coding tools responsibly when working on data-platform code? I use them to accelerate routine implementation, exploration, and test generation, but I validate all output against requirements and production constraints. For SQL, schema changes, and correctness-sensitive transformations, I review query plans, run automated tests, and verify results with representative data. AI output is an input to engineering judgment rather than a substitute for it. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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