🚀 Who we are: Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies across a wide range of industries.
🧠 About the Product:
We’re hiring for AppsFlyer — a global SaaS marketing analytics platform helping businesses measure and optimize their marketing across mobile, web, CTV, PC, and console.
The scale is huge:
150B+ mobile app events processed daily
Thousands of servers running at any given moment
Data powering analytics for global brands
Massive distributed systems handling billions of events and requests
You’ll join the Analytics group, responsible for turning this enormous amount of data into meaningful insights through complex aggregations, analytical databases, APIs, and beautiful dashboards.
🔧 What you’ll do:
Build and maintain large-scale data pipelines with Apache Airflow and Spark
Work with Scala Spark / PySpark to process billions of events
Design, model, and optimize analytical databases for high-throughput workloads
Build backend services and APIs for data ingestion, aggregation, and data delivery
Monitor production systems and troubleshoot real-world performance issues
Collaborate with Product Managers and engineering teams on complex features
Contribute to the migration toward Google Cloud Platform and BigQuery
Take ownership of features end-to-end, from design to production
Participate in on-call rotations and production incident response
Document architecture, data flows, tests, and technical decisions
Tech stack:
Big Data: Apache Spark, Scala / PySpark Orchestration: Apache Airflow Databases: Analytical databases, BigQuery Cloud: Google Cloud Platform Backend: JVM languages / Python, Go or Clojure Infrastructure: Distributed microservices, CI/CD, observability AI tools: GitHub Copilot, Cursor, ChatGPT
✅ What we’re looking for:
3+ years of hands-on experience building and operating production Big Data systems
2+ years designing and maintaining large-scale distributed data processing pipelines
Strong practical experience with Apache Spark or similar Big Data frameworks
Experience with Apache Airflow or similar workflow orchestration tools
Strong SQL skills and experience designing analytical data models
Experience with Scala, Java, Clojure, or Python for backend/data development
Experience with cloud platforms and modern data warehouses such as GCP / BigQuery
Experience owning production systems, including monitoring, troubleshooting, and incident response
Strong communication and collaboration skills
B.Sc. in Computer Science or equivalent practical experience
English — Upper-Intermediate
⭐️ Nice to have:
Production experience with Google BigQuery, ETL pipelines, and analytical workloads
Experience developing backend services in Go or Clojure
Open-source contributions
Technical conference or meetup speaking experience
Practical experience using AI-assisted development tools such as Copilot, Cursor, or ChatGPT
💡 Why this role is interesting:
Massive scale: work with a platform processing 150B+ events daily
Real Big Data challenges: distributed processing, analytical databases, performance, and scalability
Strong ownership: influence architecture and own features end-to-end
Modern stack: Spark, Airflow, GCP, BigQuery, and AI-assisted development
Cloud transformation: contribute to a major migration toward GCP and modern data tooling
Global product: your work will directly impact analytics used by businesses worldwide
Engineering culture: production ownership, observability, quality, and continuous improvement
🎁 What we offer:
Health insurance
Paid unlimited vacation days + national holidays + additional recharge days
Paid sick days
Meals reimbursement
Sport reimbursement
Mental health program
Breakfast in the office
Team buildings, happy hours, and other team activities
Snacks, fruits & ice-cold beer
Brand-new Mac laptop + 2 monitors and a Starter package for every new
