Software Engineer, Query Engine & Distributed Systems
About The Position
Conviva is the intelligence layer for digital businesses, turning every consumer interaction into outcome-based intelligence—linking engagement patterns across AI agents, apps, websites, and streaming video to real results such as purchases, bookings, and resolved support requests. Powered by its patented Time-State Technology®, the Conviva® Operational Data Platform delivers real-time insights and automation that help leading enterprises grow, improve satisfaction, and build lasting trust. Conviva engineers build and operate distributed systems that handle five trillion events every day, achieving performance at a scale comparable to the world's largest analytics platforms. We are looking for a highly motivated and self-driven backend engineer who is passionate about distributed systems, large-scale data infrastructure, and performance optimization. In this role, you will design and build core components of Conviva's real-time analytics platform, collaborating with a small, world-class team where every technical decision matters. Our engineers combine academic depth with practical innovation, contributing to research publications and advancing the state of large-scale distributed data systems.
Requirements
- BS, MS, or PhD in Computer Science or a related field.
- Strong foundation in computer science fundamentals, including algorithms, data structures, and networking.
- Proficiency in C++, Rust, Scala, Java, or similar systems programming language.
- Proven experience designing or building large-scale distributed systems, ideally in production environments.
- Hands-on experience with big data platforms and query engines (e.g., ClickHouse, Apache Druid, Presto, BigQuery, and others).
- Familiarity with distributed stream processing frameworks such as Akka Streams, Apache Spark, or Apache Flink.
- Demonstrated expertise in performance analysis and tuning for distributed systems.
- Strong collaborator with experience mentoring others, driving initiatives, and contributing to a positive engineering culture.
- Adaptable and comfortable working in a fast-paced, evolving environment.
Nice To Haves
- Experience building and scaling systems in SaaS or data infrastructure environments.
- Contributions to open-source projects in distributed systems, databases, or analytics.
- Knowledge of OLAP architecture, columnar storage, and high-performance query execution.
Responsibilities
- Design and develop our specialized, high-performance query engine layer, to handle complex stateful patterns and real-time analytics.
- Develop advanced query optimization strategies and performance modeling tools to ensure low-latency responses across trillion-event datasets.
- Architect and evolve distributed system components that prioritize scalability and fault tolerance for next-generation OLAP workloads.
- Partner with cross-functional teams to identify and unlock latent capabilities within our storage and query infrastructure.
- Refine the core data processing layer to maximize efficiency and reliability across massive, high-cardinality datasets.
- Facilitate seamless data flow by integrating high-performance analytical solutions into the broader distributed ecosystem.
- Stay up to date with advancements in distributed databases, stream processing frameworks, and cloud infrastructure, evaluating new technologies for their impact and scalability.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
251-500 employees
