Senior Software Engineer — Distributed Systems (Rust)

Role: Senior Software Engineer — Distributed Systems (Rust)

Experience: 5 - 8 Years

Education: B.Tech/Master’s

Location: Bengaluru (Work from office)

Join Our Journey at VuNet

VuNet is a pioneer in Business Journey Observability , leveraging Big Data and Machine Learning to transform digital experiences across the financial services. Our deep-tech platform provides end-to-end visibility into customer journeys — empowering proactive issue resolution, operational resilience, and superior user satisfaction.

If you’ve ever used instant payment systems like UPI, chances are you’ve already experienced the power of our platform — we monitor over 28 billion digital transactions monthly

(that’s equal to watching 3 years of tik-tok videos) , touching 300 million users with leading banks and financial institutions .

VuNet is Series B funded, part of NASSCOM DeepTech Club, awarded NASSCOM’s AI Gamechanger, recognized in Forbes DGEMS 200 and by several global analysts including Gartner, Omdia.

We’re building a new category of observability purpose-built for complex digital journeys — across payments, lending, core banking and more — already powering some of the largest banks in India and MEA.

Your Role: Senior Software Engineer — Distributed Systems (Rust)

We are building the database and cold-storage tier for observability data at petabyte scale, with a focus on making telemetry data cost-efficient to store and fast to query.

Our technology stack is centered around Rust and Apache DataFusion, and we are looking for a Senior Software Engineer who enjoys solving hard problems across distributed systems, database engines, query execution, and storage.

You will have the opportunity to shape the architecture of a critical data platform from the ground up and work on systems that ingest and query logs, metrics, and traces.

Roles & Responsibilities

• Design and build scalable and reliable systems for storing and querying observability data.
• Build database and storage components using Rust and Apache DataFusion.
• Work across the query engine and storage layers, including query planning, execution, optimization, and data access.
• Design distributed systems for high throughput, low latency, fault tolerance, and horizontal scalability.
• Work with columnar and analytical data formats such as Apache Arrow and Parquet.
• Optimize query performance across CPU, memory, I/O, and network boundaries.
• Design systems for efficient cold-tier storage, balancing storage cost, query performance, and data retention requirements.
• Build production-grade systems with strong observability, reliability, and operational characteristics.
• Participate in architecture and design reviews and make pragmatic technology trade-offs.

What we are looking for

• 5+ years of software engineering experience, with significant time spent on backend or infrastructure systems.
• At least 3 years of hands-on Rust programming, including production systems you have shipped and operated. This is a hard requirement.
• Strong understanding of distributed systems and database fundamentals.
• Hands-on experience with one or more of: Query engines, Databases, Distributed storage, Data processing systems, Search/indexing systems, Analytics platforms
• Strong understanding of concurrency, parallelism, memory management, and networking.
• Strong understanding of data structures, algorithms, and system design.
• Experience with Kubernetes — deploying, operating, and debugging stateful workloads in production.
• Strong debugging and performance-profiling skills.
• Experience taking systems from design through to reliable operation at scale.

Good to Have

• Experience with Apache DataFusion or other query engines such as Spark, Trino, DuckDB, ClickHouse, or Velox.
• Experience contributing to or working with open-source database/query-engine projects.
• Experience with Go.
• Experience with observability systems and telemetry data, particularly logs, metrics, and traces.
• Experience with time-series or analytical databases.
• Familiarity with Apache Arrow, Parquet, Delta Lake, or Iceberg.
• Experience with cloud object storage such as S3, GCS, or Azure Blob Storage, including compaction, indexing, and tiered storage over object stores.
• Experience with cloud-native infrastructure beyond Kubernetes itself — operators, service meshes, and cloud-native storage and networking.