Data Engineer

Adaptiq, on behalf of AppsFlyer, is looking for a Data Engineer

About AppsFlyer (Kyiv):

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 micro-services, backends, and infrastructure, 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 in AppsFlyer’s Analytics group, you will be responsible for the full lifecycle of event data — from ingestion and processing to storage, modeling, and delivery through APIs.

You will build and maintain data pipelines with Apache Airflow and Spark, evaluate and optimize analytical databases, and integrate new components within a hybrid microservices architecture. You will work closely with product managers and cross-functional engineering teams, handle production issues, and take part in the company’s migration toward Google Cloud and BigQuery.

This role provides a high level of ownership over feature design, direct impact on a platform processing billions of events every day, and opportunities to contribute to open-source initiatives or share expertise at industry events.
 

Key Responsibilities:

• Develop and support data processing pipelines using Apache Airflow, Scala Spark, or PySpark.
• Select, design, and optimize analytical databases for high-volume, low-latency queries.
• Build backend services and APIs for data ingestion, aggregation, and customer-facing data consumption.
• Monitor system reliability and performance, investigate issues, and resolve production incidents.
• Partner with product managers and engineering teams to plan, design, and deliver complex features.
• Support migration initiatives to Google Cloud Platform, BigQuery, and modern data technologies.
• Participate in on-call rotations, PagerDuty alerts, and incident response processes.
• Document architecture, data flows, and technical decisions while maintaining high code quality and test coverage.
   

Required Competence and Skills:

• 3+ years of software development experience with a strong focus on data engineering.
• Hands-on experience with Apache Spark, using either Scala or PySpark.
• Practical experience with Apache Airflow.
• Background in building and maintaining distributed data systems with high throughput and low latency.
• Strong SQL knowledge and experience with data modeling for analytical use cases.
• Experience with JVM-based languages such as Scala, Java, or Clojure, or Python for backend development.
• Experience with cloud platforms, preferably GCP, and data warehouses such as BigQuery.
• Proven ownership of production systems, including on-call responsibilities and incident management.
• Strong English communication skills for working in a distributed environment.
• B.Sc. in Computer Science or equivalent practical experience.
   

Nice to Have:

• Production experience with large-scale databases and ETL tools.
• Hands-on experience with backend services written in Go or Clojure.
• Experience building production-grade BigQuery ETL processes and data pipelines.
• Contributions to open-source projects or experience speaking at meetups, conferences, or industry events.
• An AI-oriented mindset, including familiarity with tools such as GitHub Copilot and modern AI-assisted workflows.
  
  Benefits Package:
• Health insurance.
• Paid unlimited vacation days, national holidays, and additional recharge days.
• Meal reimbursement.
• Sport reimbursement.
• Breakfast in the office.
• Mental health program.
• Team buildings, happy hours, and other team activities.
• Paid sick leave.
• Snacks, fruits, and ice-cold beer in the office.
• Brand-new Mac laptop, two monitors, and a starter package for every new team member.