Senior Software Engineer

About the role

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, Java, 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:

- 5+ 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 platforms (AWS, GCP, Azure, CDP, MapR, or similar).

- Hands-on AWS experience, especially with S3 and EMR/EMR Serverless (Athena is a strong advantage).

- Experience building and operating cloud-based, high-scale distributed systems.

- Strong analytical and interpersonal skills, with the ability to work effectively across engineering and business teams.

- Professional spoken and written English.

Bonus Points:

- Knowledge of Scala is a plus.

- Experience with the Hadoop ecosystem and distributed data processing platforms (AWS EMR, GCP Dataproc, Azure Cosmos, CDP, MapR, Databricks, or similar).

- Hands-on AWS experience, especially with S3 and EMR/EMR Serverless.

- Experience with CI/CD pipelines and tooling.

- Experience with the Hadoop ecosystem and distributed data processing platforms (AWS, GCP, Azure, CDP, MapR, or similar).

- Hands-on AWS experience, especially with S3 and EMR/EMR Serverless.

- Experience building and operating cloud-based, high-scale distributed systems.