Scala Developer

Job Description

Design and develop scalable distributed systems using Scala for high-throughput backend services.

• Build and maintain large-scale data processing pipelines using Apache Spark in production environments.
• Develop real-time and batch data processing workflows including Spark Structured Streaming solutions.
• Design and implement cloud-native applications deployed on Google Cloud Platform.
• Build event-driven architectures using messaging and streaming systems.
• Develop frontend applications using functional reactive UI architecture with Laminar.
• Implement shared type-safe models across backend and frontend systems.
• Optimize system performance across JVM, Spark, and distributed compute layers.
• Work on Kubernetes-based deployments and containerized microservices architecture.
• Collaborate with platform, data engineering, and infrastructure teams on system design and scaling.
• Perform debugging, performance tuning, and production support for distributed systems.
• Contribute to architecture decisions for high-scale, low-latency data platforms.

Note:

PySpark-only profiles will not be considered.

• 10+ years of software engineering experience
• 6+ years of production experience with Scala
• 6+ years of hands-on experience with Apache Spark using Scala
• Strong expertise in JVM internals, memory management, and performance tuning
• Deep understanding of functional programming principles (immutability, higher-order functions, monads)
• Strong experience in concurrent and distributed system design
• Strong experience with Spark Structured Streaming
• Deep understanding of Spark internals (Catalyst optimizer, Tungsten execution engine)
• Experience handling multi-terabyte distributed workloads
• Strong knowledge of columnar data formats (Parquet, Avro, ORC)
• Experience with Delta Lake or Apache Iceberg (preferred)
• Experience with event streaming systems such as Apache Kafka
• Strong production experience on Google Cloud Platform
• Hands-on experience with Google Kubernetes Engine, Dataproc, Big Query, Pub/Sub, Cloud Storage
• Experience with Terraform and infrastructure-as-code on Google Cloud Platform
• Strong Kubernetes and container orchestration experience
• Production experience building UIs using functional reactive programming with Laminar
• Strong understanding of FRP (Functional Reactive Programming), reactive streams and event-driven UI design
• Experience building complex single-page applications using Laminar
• Experience designing shared domain models between frontend and backend
• Experience integrating frontend UI with REST/gRPC backend services
• Knowledge of SBT multi-module builds for frontend-backend shared codebases
• Understanding of type-safe frontend architecture patterns in Scala ecosystem
• Experience with UI state management in functional programming style
• Experience with Akka clustered systems
• Strong understanding of event sourcing, CQRS architecture, eventually consistent systems, CAP theorem trade-offs
• Experience designing fault-tolerant distributed systems
• Experience with microservices architecture at scale
• Experience with Cats Effect, ZIO, FS2, Monix
• Advanced functional programming design patterns
• Tagless-final architecture (preferred)
• JVM garbage collection tuning (G1, ZGC)
• Spark job optimization and cluster tuning
• Linux system-level performance troubleshooting
• Distributed system resource optimization
• Scala 3 experience
• Monocle optics library
• Graal
  
  VM native image compilation
• Internal platform dashboard development using Laminar
• Open-source Scala ecosystem contributions