Senior Software Engineer

Sibros; Pune District; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Sibros is seeking a Senior Software Engineer to scale backend systems powering Deep Logger's data pipeline, from ingestion to storage and ML model integration.

You will collaborate with firmware, data science, and product teams to deliver high-throughput, low-latency solutions capable of handling billions of events daily, while ensuring reliability and regulatory compliance.

Qualifications

• 7+ years of software engineering experience with distributed systems.
• Strong CS fundamentals: data structures, algorithms, concurrency, distributed computing.
• Experience designing large-scale, low-latency data systems for real-time and batch processing.
• Hands-on with event-driven architectures and messaging systems like Kafka or Pub/Sub.
• Proficient in Go or Java and cloud-native infrastructure.

Responsibilities

• Design and evolve scalable data pipelines for real-time and batch processing.
• Mentor engineering team and drive best practices.
• Collaborate across firmware, frontend, product, and data science teams.
• Drive innovation with open-source or cloud-native tools.
• Own reliability, scalability, SLAs/SLOs, and incident postmortems.
• Contribute to strategic technical direction and cost optimization.

Skills

Distributed systems

Go/Java production code

Real-time data processing

Low-latency systems

Data pipelines

Mentoring/leadership

Tools

Apache Kafka

Apache Beam

Google Cloud Dataflow

Pub/Sub

Cloud-native infrastructure

Job description

Job Summary

Job Title: Senior Software Engineer

Reporting to: Engineering Manager

Experience: 6 - 9 years

At Sibros, we are building the foundational data infrastructure that powers the software-defined future of mobility. One of our most impactful products-Deep Logger-enables rich, scalable, and intelligent data collection from connected vehicles, unlocking insights that were previously inaccessible.

Our platform ingests high-frequency telemetry, diagnostic signals, user behavior, and system health data from vehicles across the globe. We transform this into actionable intelligence through real-time analytics, geofence-driven alerting, and predictive modeling for use cases like trip intelligence, fault detection, battery health, and driver safety.

We are looking for a Senior Software Engineer to help scale the backend systems that support Deep Logger's data pipeline-from ingestion and streaming analytics to long-term storage and ML model integration. You will play a key role in designing high-throughput, low-latency systems that operate reliably in production, even as data volumes scale to billions of events per day.

In this role, you will collaborate across firmware, data science, and product teams to deliver solutions that are not only technically robust, but also critical to safety, compliance, and business intelligence for OEMs and fleet operators.

This is a unique opportunity to shape the real-time intelligence layer of connected vehicles, working at the intersection of event-driven systems, cloud-native infrastructure, and automotive-grade reliability.

What you will do

• Lead the Design and Evolution of Scalable Data Systems: Architect end-to-end real-time and batch data processing pipelines that power mission-critical applications such as trip intelligence, predictive diagnostics, and geofence-based alerts. Drive system-level design decisions and guide the team through technology tradeoffs.
• Mentor and Uplift the Engineering Team: Act as a technical mentor to junior and mid-level engineers. Conduct design reviews, help grow data engineering best practices, and champion engineering excellence across the team.
• Partner Across the Stack and the Org: Collaborate cross-functionally with firmware, frontend, product, and data science teams to align on roadmap goals. Translate ambiguous business requirements into scalable, fault-tolerant data systems with high availability and performance guarantees.
• Drive Innovation and Product Impact: Shape the technical vision for real-time and near-real-time data applications. Identify and introduce cutting-edge open-source or cloud-native tools that improve system reliability, observability, and cost efficiency.
• Operationalize Systems at Scale: Own the reliability, scalability, and performance of the pipelines you and the team build. Lead incident postmortems, drive long-term stability improvements, and establish SLAs/SLOs that balance customer value with engineering complexity.
• Contribute to Strategic Technical Direction: Provide thought leadership on evolving architectural patterns, such as transitioning from streaming-first to hybrid batch-stream systems for cost and scale efficiency. Proactively identify bottlenecks, tech debt, and scalability risks.

What you should know

• 7+ years of experience in software engineering with a strong emphasis on building and scaling distributed systems in production environments.
• Deep understanding of computer science fundamentals including data structures, algorithms, concurrency, and distributed computing principles.
• Proven expertise in designing, building, and maintaining large-scale, low-latency data systems for real-time and batch processing.
• Hands-on experience with event-driven architectures and messaging systems like Apache Kafka, Pub/Sub, or equivalent technologies.
• Strong proficiency in stream processing frameworks such as Apache Beam, Flint, or Google Cloud Dataflow, with a deep appreciation for time and windowing semantics, backpressure, and checkpointing.
• Demonstrated ability to write production-grade code in Go or Java, following clean architecture principles and best practices in software design.
• Solid experience with cloud-native infrastructure.