Staff Software Engineer

Bosch Global Software Technologies Pvt Ltd; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Bosch Global Software Technologies Pvt Ltd in Bengaluru is seeking experienced engineers to design and own end-to-end architectures across microservices, data platforms, and event-driven systems. You will build scalable backend services, APIs, and cloud-native infrastructure with Kubernetes, emphasizing observability, CI/CD, and reliability.

The role requires mentoring engineers, leading design reviews, and delivering robust data pipelines using Spark/Databricks where needed.

Qualifications

• 8+ years of professional software engineering experience across backend, platform and/or data domains.
• Strong programming skills in Scala or Java (Scala preferred).
• Proven experience building distributed microservices and event-driven systems in the Scala/JVM ecosystem.
• Hands-on experience with Kafka in production at scale.
• Solid API design experience (REST and/or event-driven).
• Strong knowledge of relational databases (PostgreSQL), data modeling and query optimization.
• Experience building distributed data pipelines with Spark and/or Databricks.
• Demonstrated ability to lead technical design and architecture decisions across teams.
• Experience mentoring and growing engineers.

Responsibilities

• Design and own end-to-end architectures across microservices, event-driven systems, and data platforms.
• Build and deliver backend services and APIs that are reliable, secure, and scalable.
• Design and operate cloud-native infrastructure on Kubernetes with platform engineering best practices.
• Build observability into systems with logs, metrics, tracing, and SLOs.
• Deliver through CI/CD with safe release and rollback strategies.
• Lead architecture reviews and author lightweight design documents.
• Coach engineers through reviews, sessions, and pairing.

Skills

Scala/Java

Kafka

Spark

Databricks

Kubernetes

REST APIs

CI/CD

Observability

Mentoring

Platform engineering

Tools

KStreams

Flink

cats-effect

fs2

tapir

PostgreSQL

Spark

Databricks

Job description

Roles & Responsibility:

• Design and own end-to-end architectures across microservices, event-driven systems, and data platforms.


• Build and deliver high-quality backend services and APIs that are reliable, secure, and scalable.


• Design and operate cloud-native infrastructure on Kubernetes, applying platform engineering best practices.


• Build and maintain data pipelines and products on Spark and Databricks where required.


• Drive event-driven architecture using Kafka and streaming technologies.


• Write clean, testable, and maintainable software primarily in Scala with Python where appropriate.


• Lead architecture and design reviews; author lightweight design documents for major decisions.


• Define and improve engineering standards across testing, observability, CI/CD, and reliability.


• Coach and mentor engineers at multiple levels through reviews, design sessions, and pairing.


• Build observability into systems from day one (logs, metrics, tracing, alerting, SLOs).


• Deliver through CI/CD with safe release, rollback, and progressive delivery strategies.

Skills

• 8+ years of professional software engineering experience across backend, platform and or data domains.


• Strong programming skills in Scala or Java (Scala preferred); other languages are a plus.


• Proven experience building distributed microservices and event-driven systems ideally in the Scala / JVM ecosystem (we use KStreams, Flink, cats-effect, fs2 & tapir)


• Hands-on experience with Kafka in production at scale.


• Solid experience designing and developing APIs (REST and/or event-driven interfaces).


• Strong knowledge of relational databases (e.g. PostgreSQL), data modeling, and query optimization.


• Experience building distributed data pipelines with Spark and/or Databricks.


• Demonstrated ability to lead technical design and architecture decisions across teams.


• Experience mentoring and growing engineers.

Good To Have:

• Working knowledge of Kubernetes - workloads, networking, Helm, scaling, and operational practices.


• Experience with data governance, lakehouse table formats (Delta, Iceberg), and modern data platforms.


• Experience with platform engineering - building developer platforms, golden paths, or internal tooling.


• Performance profiling and JVM tuning experience.


• Experience with MLOps or data science platform integrations.