Senior Software Engineer (Data Platform)

About the Role

Job Title: Senior Software Engineer

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 d

• oLead 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 experienc

  e in software engineering with a strong emphasis on building and scaling distributed systems in production environments

• .Deep understanding of computer science fundamental

  s including data structures, algorithms, concurrency, and distributed computing principles
• .Proven expertise in designing, building, and maintaining

  large-scale, low-latency data system

  s for real-time and batch processing

• .Hands-on experience with event-driven architecture

  s and messaging systems like

  Apache Kafk

  a,

  Pub/Su

  b, or equivalent technologies
• .Strong proficiency in

  stream processing framework

  s such as

  Apache Bea

  m,

  Flin

  k, or

  Google Cloud Dataflo

  w, with a deep appreciation for time and windowing semantics, backpressure, and checkpointing
• .Demonstrated ability to write

  production-grade code in Go or Jav

  a, following clean architecture principles and best practices in software design
• .Solid experience with

  cloud-native infrastructur

  e including

  Kubernete

  s, 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 stack

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

  balance pragmatism with technical rigo

  r, 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 domain

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

.Preferred Qualification

• sExperience architecting and building systems for

  large-scale IoT or telemetry-driven application

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

  streaming and batch data processing paradigm

  s, using tools such as

  Apache Kafk

  a,

  Apache Flin

  k,

  Apache Bea

  m, or

  Google Cloud Dataflo

  w
• .Hands-on experience with

  cloud-native architecture

  s on platforms like

  Google Cloud Platform (GCP

  ),

  AW

  S, or

  Azur

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

  high-performance time-series or analytical database

  s such as

  ClickHous

  e,

  Apache Drui

  d, or

  InfluxD

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

  resilient, fault-tolerant pipeline

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

  schema evolution, data contract

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

  geospatial dat

  a, 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 and benefits
• .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