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Senior Software Engineer (Data Platform)

6 - 9 years

13 - 17 Lacs

Posted:23 hours ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Sibros is accelerating the future of SDV excellence with its Deep Connected Platform that orchestrates full vehicle software update management, vehicle analytics, and remote commands in one integrated system. Adaptable to any vehicle architecture, Sibros platform meets stringent safety, security, and compliance standards, propelling OEMs to innovate new connected vehicle use cases across fleet management, predictive maintenance, data monetization, and beyond.

Learn more at www.sibros.tech .

Our Mission

Our mission is to help our customers get the most value out of their connected devices.

Follow us on

LinkedIn | Youtube | Instagram

About the Role:

Job Title: Senior Software Engineer

Reporting to: Engineering Manager

Location: Pune, India

Job Type: Full-Time

Experience: 6 - 9 years

Deep Logger

high-frequency telemetry

Senior Software Engineer

In this role, you ll 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.

real-time intelligence layer of connected vehicles

What you ll 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

    ,

    Flink

    , 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

    including

    Kubernetes

    , serverless compute (e.g., AWS Lambda, GCP Cloud Functions), and containerized deployments using CI/CD pipelines.
  • Proficiency with cloud platforms, especially

    Google Cloud Platform (GCP)

    or

    Amazon Web Services (AWS)

    , and services like BigQuery, S3/GCS, IAM, and managed Kubernetes (GKE/EKS).
  • Familiarity with

    observability stacks

    (e.g., Prometheus, Grafana, OpenTelemetry) and an understanding of operational excellence in production environments.
    Ability to

    balance pragmatism with technical rigor

    , navigating ambiguity to design scalable and cost-effective solutions.
  • Passionate about building platforms that empower internal teams and deliver meaningful insights to customers, especially within the

    automotive, mobility, or IoT domains

    .
  • Strong communication and collaboration skills, with experience working closely across product, firmware, and analytics teams.

Preferred Qualifications

  • Experience architecting and building systems for

    large-scale IoT or telemetry-driven applications

    , including ingestion, enrichment, storage, and real-time analytics.
  • Deep expertise in both

    streaming and batch data processing paradigms

    , using tools such as

    Apache Kafka

    ,

    Apache Flink

    ,

    Apache Beam

    , or

    Google Cloud Dataflow

    .
  • Hands-on experience with

    cloud-native architectures

    on platforms like

    Google Cloud Platform (GCP)

    ,

    AWS

    , or

    Azure

    , leveraging services such as Pub/Sub, BigQuery, Cloud Functions, Kinesis etc.
  • Experience working with

    high-performance time-series or analytical databases

    such as

    ClickHouse

    ,

    Apache Druid

    , or

    InfluxDB

    , optimized for millisecond-level insights at scale.
  • Proven ability to design

    resilient, fault-tolerant pipelines

    that ensure data quality, integrity, and observability in high-throughput environments.
  • Familiarity with

    schema evolution, data contracts

    , and streaming-first data architecture patterns (e.g., Change Data Capture, event sourcing).
  • Experience working with

    geospatial data

    , telemetry, or real-time alerting systems is a strong plus.
  • Contributions to open-source projects in the data or infrastructure ecosystem, or active participation in relevant communities, are valued.

What We Offer:

  • Competitive compensation package with performance incentives.
  • A dynamic work environment with a flat hierarchy and the opportunity for rapid career advancement.
  • Collaborate with a dynamic team that s passionate about solving complex problems in the automotive IoT space.
  • Access to continuous learning and development opportunities.
  • Flexible working hours to accommodate different time zones.
  • Comprehensive benefits package including health insurance and wellness programs.
  • A culture that values innovation and promotes a work-life balance.

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Sibros
Sibros

Automotive Technology

San Mateo

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