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🚀 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 team member