(Big) Data Engineer

About AppsFlyer:

AppsFlyer provides a SaaS marketing analytics platform that measures and optimizes marketing activities across mobile, web, CTV, PC, and console applications. AppsFlyer is known for its massive backend production. At any given moment, thousands of servers are consuming 150+ billion mobile app events, crunching our users’ data, serving requests, and communicating on a massive scale.

To maintain the universe we call AppsFlyer, we practice modern production operations with a complete self-serve CI/CD platform, a highly integrated observability stack for our microservices, backends, and infrastructure, and a culture of ownership and eagerness for quality.

The Analytics group is responsible for showing our clients the stories their data is telling. Through complex aggregation, mission-tailored analytical databases, and carefully crafted APIs, we are able to provide slice-and-dice analysis in our beautiful dashboards and through the use of external integrations.

About the Role:

As a Data Engineer(Big Data) within the Analytics group at AppsFlyer, you will own the end-to-end journey of event data - from ingestion and processing to storage, modeling, and API delivery. 

You will design and implement data pipelines using Apache Airflow and Spark, choose and optimize analytical databases, and integrate new components in our hybrid microservices environment. You will collaborate with product managers and cross-functional teams, troubleshoot production incidents, and influence our migration toward Google Cloud and BigQuery. This role offers autonomy over feature design, real impact on a platform handling billions of events daily, and the chance to contribute to open-source projects or speak at industry forums.

Key Responsibilities:

• Develop and maintain data processing pipelines using Apache Airflow, Scala Spark or PySpark.
• Select, model and optimize analytical databases for high-throughput, low-latency queries.
• Design and implement backend services and APIs for data ingestion, aggregation and client consumption.
• Monitor system performance and stability; diagnose and resolve production issues.
• Collaborate with product managers and engineers to plan and deliver complex features.
• Drive migration efforts to Google Cloud Platform, BigQuery and modern data tooling.
• Participate in on-call rotations, alerting via PagerDuty and incident response procedures.
• Document system architecture and data flows; maintain code quality and tests.

Required Competence and Skills:

• 3+ years of hands-on experience building and operating production Big Data systems
• 2+ years of proven experience designing, developing, and maintaining large-scale distributed data processing pipelines
• Strong practical experience with distributed data processing technologies such as Apache Spark or equivalent Big Data frameworks.
• Experience with workflow orchestration tools such as Apache Airflow or similar.
• Strong SQL skills and experience designing data models for analytical workloads.
• Familiarity with JVM languages (Scala, Java, Clojure) or Python for backend development.
• Experience working with cloud platforms and modern data warehouses like Google Cloud Platform and BigQuery or similar.
• Experience owning production systems, including monitoring, troubleshooting, and responding to production incidents.
• Strong communication skills and ability to collaborate effectively within distributed engineering teams.
• B.Sc. in Computer Science or equivalent practical experience.

Nice to Have:

• Production experience with Google BigQuery, including ETL pipelines and analytical workloads.
• Experience developing backend services in Go or Clojure.
• Experience contributing to open-source projects or presenting at technical conferences or meetups.
• An AI mindset, including practical use of tools such as GitHub Copilot, Cursor, ChatGPT, or similar AI-assisted development workflows.

Benefits Package includes:

• 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