Description
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:
- 3+ years of development experience with a passion for excellence
- Experience in JVM languages
- Hands-on background with production systems
- Experience in building APIs for server-client applications
- Strong SQL knowledge
- Ability to grasp new languages, systems, and frameworks quickly
- A team player with the drive to get things done and lead others along the way
- Good communication skills, spoken and written English
- Desire to switch into the Big Data domain and learn its stack.
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).
- Experience building and operating cloud-based, high-scale distributed systems.
- Referred by an AppsFlyer employee.
Benefits:
- Health Insurance
- Paid Unlimited Vacation Days + all national holidays + additional recharge days
- Meals Reimbursement
- Sport Reimbursement
- Breakfast in the office
- Mental health program
- Team building, happy hours, and other team activities
- Paid sick days
- Snacks, fruits & ice cold beer
- All new team members are provided with a brand-new Mac laptop with 2 monitors and a Starter package