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 <h3> Key technologies include:</h3> <ul> <li>Processing and streaming: Spark, Kafka</li> <li>Data lake and formats: S3, Parquet, Delta Lake, Iceberg, Hadoop, Hive</li> <li>Cloud and compute:** AWS, EMR/EMR Serverless, Athena</li> <li>Analytics and data platforms:** BigQuery, BigLake, Aerospike, AWS Glue, Databricks Delta Engine</li> <li>Languages: Scala, Java, plus a broader polyglot engineering environment across AppsFlyer</li> </ul> <h3>What you’ll do:</h3> <ul> <li>Design, build, and evolve large-scale data pipelines from raw ingestion to production-ready datasets.</li> <li>Develop and maintain Spark/Scala-based data processing workflows for both batch and streaming use cases.</li> <li>Own data platform reliability, quality, and performance in production environments.</li> <li>Collaborate with engineers, product owners, and stakeholders to define and deliver robust data solutions.</li> <li>Help shape engineering standards and operational practices as the DataOS team grows.</li> </ul> What You Bring: <ul> <li>5+ years of software engineering experience, with strong hands-on Scala and/or Java development.</li> <li>Strong Java core fundamentals</li> <li>Proven experience with Spark and Kafka in production environments.</li> <li>Experience with the Hadoop ecosystem and distributed data processing platforms (AWS, GCP, Azure, CDP, MapR, or similar).</li> <li>Hands-on AWS experience, especially with S3 and EMR/EMR Serverless (Athena is a strong advantage).</li> <li>Experience building and operating cloud-based, high-scale distributed systems.</li> <li>Strong analytical and interpersonal skills, with the ability to work effectively across engineering and business teams.</li> <li>Professional spoken and written English.</li> </ul> Bonus Points: <ul> <li>Knowledge of Scala is a plus.</li> <li>Experience with the Hadoop ecosystem and distributed data processing platforms (AWS EMR, GCP Dataproc, Azure Cosmos, CDP, MapR, Databricks, or similar).</li> <li>Hands-on AWS experience, especially with S3 and EMR/EMR Serverless.</li> <li>Experience with CI/CD pipelines and tooling.</li> <li>Experience with the Hadoop ecosystem and distributed data processing platforms (AWS, GCP, Azure, CDP, MapR, or similar).</li> <li>Hands-on AWS experience, especially with S3 and EMR/EMR Serverless.</li> <li>Experience building and operating cloud-based, high-scale distributed systems.</li> <li>Referred by an AppsFlyer employee.</li> </ul> Benefits: <ul> <li>Health Insurance</li> <li>Paid Unlimited Vacation Days + all national holidays + additional recharge days</li> <li>Meals Reimbursement</li> <li>Sport Reimbursement</li> <li>Breakfast in the office</li> <li>Mental health program</li> <li>Team building, happy hours, and o

Senior Software Engineer

Job Description