Software Engineer
Posted 3 Sep 2026
Advertised as “Senior Software Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
Compensation
No salary listed for this role.
Role speciality
Data EngineeringDistributed Systems
Useful technologies
AerospikeAthenaAWSAWS GlueAzureAzure CosmosBigLakeBigQueryCDPDatabricksDatabricks Delta EngineDelta LakeEMREMR ServerlessGCPGCP DataprocHadoopHiveIcebergJavaKafkaMacMapRParquetS3ScalaSpark
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).