Software Engineer
AppsFlyer - Kyiv
Posted Mar 19, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Software Engineer Kyiv The DataOS team at AppsFlyer is building and operating a reliable, high-scale data platform that powers analytics and product capabilities across the company. We process more than 150 billion events per day and manage petabyte-scale historical data. Our team owns much more than a traditional "data lake" - including schema management, ETL pipelines, and interfaces to and from storage. If you're excited by scale, ownership, and building production-grade data systems, we'd love to meet you. Tech stack highlights Key technologies include: - Processing and streaming: Spark, Kafka - Data lake and formats: S3, Parquet, Delta Lake, Iceberg, Hadoop, Hive - Cloud and compute:** AWS, EMR/EMR Serverless, Athena - Analytics and data platforms:** BigQuery, BigLake, Aerospike, AWS Glue, Databricks Delta Engine - Languages: Scala, Python (team focus), plus a broader polyglot engineering environment across AppsFlyer What you'll do: - Design, build, and evolve large-scale data pipelines from raw ingestion to production-ready datasets. - Develop and maintain Spark/Scala-based data processing workflows for both batch and streaming use cases. - Own data platform reliability, quality, and performance in production environments. - Collaborate with engineers, product owners, and stakeholders to define and deliver robust data solutions. - Help shape engineering standards and operational practices as the DataOS team grows. What You Bring: - 3+ years of software engineering experience, with strong hands-on Scala and/or Java development. - Strong Java core fundamentals. - Proven experience with Spark and Kafka in production environments. - Experience with the Hadoop ecosystem and distributed data processing
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