About the role
We are building the next generation of large-scale recommendation and personalization platforms that power data-driven experiences across multiple business domains.
As a Senior Java Engineer, you will operate at the intersection of distributed systems, high-volume data processing, and production machine learning. This role is designed for engineers who thrive in complex environments, enjoy solving deep scalability challenges, and want to influence architecture and engineering excellence at scale.
You will play a key role in bridging data science innovation with reliable production systems, enabling high-performance ML pipelines and resilient microservice architectures that serve millions of users.
What you'll do
- Design, develop, and maintain high-performance backend services using Java and Spring Boot
- Build and optimize large-scale data processing pipelines using Apache Spark and Spark SQL
- Contribute to the architecture and implementation of distributed systems and data-driven platforms
- Collaborate closely with data scientists and ML engineers to productionize machine learning models
- Develop and maintain high-scale recommendation and personalization engines
- Ensure clean, maintainable, and well-tested code, applying best practices and design patterns
- Improve system performance, scalability, and reliability in enterprise production environments
- Participate in technical design discussions and contribute to long-term platform evolution
- Support orchestration and automation of data workflows
- Mentor engineers and promote strong engineering standards within the team
What we're looking for
- Strong hands-on experience with Java and backend engineering
- Solid knowledge of design patterns, clean code principles, and software architecture
- Proven experience building and operating distributed systems
- Strong experience within the JVM ecosystem
- Practical experience with Big Data processing, including: Apache Spark, Spark SQL
- Mandatory experience working in enterprise-level production environments
- Experience building scalable backend platforms and microservices
- Strong problem-solving mindset and ownership attitude
Nice to have
- Experience deploying machine learning models in production environments
- Knowledge of Python
- Experience with Apache Airflow for data orchestration
- Understanding of A/B testing methodologies
- Exposure to AWS SageMaker
- Experience with cloud-based data platforms and ML pipelines
Perks and benefits
- Private medical insurance
- National holidays off, even when falling on weekends
- Loyalty leave: +1 day/year
- Continuous professional development opportunities
- Sports subscription programs
- Referral bonuses for bringing in new talent
- Meal tickets
- Bookster subscription for reading & learning
- Community and team-building events
- Flexible and unlimited remote work policy
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