About the role
Design and implement core components of the audience segmentation platform
Develop and evolve a flexible segment definition language supporting complex targeting scenarios
Build scalable evaluation engines for processing large-scale entity and relationship data
Implement relationship-based audience resolution across multiple entity types
Optimize incremental recomputation for continuous data changes
Create event-driven pipelines for real-time segment accuracy
Ensure governance, auditability, and lifecycle traceability of segments
Design low-latency resolution services for high-scale operations
Develop caching strategies for dynamic segments and snapshots
Optimize system performance, scalability, and operational efficiency
Collaborate with product and engineering teams to define platform capabilities and architecture
Provide technical leadership and contribute to architectural decisions
At least 5 years of commercial software engineering experience
Strong Java expertise
Solid understanding of streaming architectures and stateful stream processing using technologies such as Apache Beam, Apache Flink, Kafka Streams, or Spark Structured Streaming
Strong experience designing and building rule engines, expression evaluators, query engines, or policy/targeting systems
Hands-on experience with incremental computation and materialized view maintenance
Experience designing event-driven distributed systems with a strong focus on scalability and reliability
Strong knowledge of data consistency concepts, including point-in-time snapshots, exactly-once processing, idempotency, bounded staleness, and eventual consistency
Experience building dependency graphs, composition engines, or DAG-based processing pipelines
Practical experience with distributed data stores and low-latency data modeling
Strong knowledge of Java and Google Cloud Platform, including Pub/Sub and Apache Beam
Experience building correctness-critical systems with a strong focus on testing, validation, and fault tolerance
Solid understanding of versioning, rollback strategies, anomaly detection, and production safety practices
Upper-Intermediate English level
WILL BE A PLUS
Experience with AdTech, MarTech, CRM segmentation, audience-building, or campaign targeting platforms
Experience with query optimization, indexing strategies, and database internals
Knowledge of graph processing, relationship traversal, or projection-based systems
Experience with multi-tenant architectures, workload isolation, and cost optimization
Understanding of GDPR-compliant data deletion and privacy propagation
Experience working in regulated domains such as Education (K-12), Healthcare, or FinTech
Experience with Google Cloud Spanner or similar globally distributed databases
Familiarity with geospatial indexing and location-based querying
PERSONAL PROFILE
Proactive and detail-oriented
Thrives in collaborative environments
Enjoys solving complex integration challenges
Comfortable experimenting with new technologies
Committed to improving data systems
We at Sigma Software are looking for a Senior Java Engineer to join an exciting project in the domain of audience segmentation and engagement. This is a remote role open to candidates from Ukraine and Europe, offering the opportunity to work with cutting-edge technologies and high-scale systems.
You will be part of a team building a real-time platform that powers communications, personalization, automation, and customer engagement across diverse ecosystems. At Sigma Software, we value innovation, collaboration, and technical excellence.
Why join us? You’ll work on challenging tasks, contribute to architectural decisions, and have the freedom to experiment with new technologies while improving data systems at scale.
CUSTOMER
Our customer is a leading EdTech company that uses AI and data-driven technologies to personalize learning experiences, optimize user engagement, and improve marketing effectiveness through advanced audience targeting and analytics.
PROJECT
The project is a real-time platform that enables product teams and business stakeholders to define and manage dynamic user groups based on user attributes, relationships, behavioral events, and historical activity.
Originally posted on Himalayas