Senior Staff Engineer - Backend & Data Engineering
Bengaluru, Karnataka, India
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingLead architecture and development of cloud data infrastructure supporting real-time health operations dashboards and telematics analytics
Own the health operations dashboard platform—design real-time data aggregation, time-series analytics, and operational dashboards for internal teams
Own the health operations dashboard platform, including real-time aggregation and time-series analytics
Design and operate Spark/Scala pipelines on Amazon EMR, orchestrated with Airflow
Architect and operate production Cassandra clusters for time-series workloads
Design streaming pipelines on Kinesis and Flink for real-time health events and alerting
Lead design reviews, mentor engineers, and investigate production incidents
From the employer’s posting
Lead architecture and development of cloud data infrastructure supporting real-time health operations dashboards and telematics analytics
Own the health operations dashboard platform—design real-time data aggregation, time-series analytics, and operational dashboards for internal teams
Design and operate scalable data pipelines on Amazon EMR (Apache Spark/Scala) orchestrated with Apache Airflow
Architect and operate production Apache Cassandra clusters for operational data and time-series workloads
Design streaming pipelines on Amazon Kinesis and Apache Flink for real-time health event processing, status aggregation, and operational alerting
Lead design reviews, mentor engineers, investigate production incidents
What you’ll bring
All qualificationsCore experience
- 6-10 years hands-on backend engineering with deep expertise in Java, Spring, and Spring Boot
- Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch
- Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization
- Solid understanding of distributed systems: retries, idempotency, fault tolerance, eventual consistency
- Experience with real-time analytics systems or operational dashboards
- Ability to debug complex production issues across services, jobs, and data stores; experience mentoring engineers
Qualification wording
6-10 years hands-on backend engineering with deep expertise in Java, Spring, and Spring Boot
Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch
Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization
Solid understanding of distributed systems: retries, idempotency, fault tolerance, eventual consistency
Experience with real-time analytics systems or operational dashboards
Ability to debug complex production issues across services, jobs, and data stores; experience mentoring engineers
Tools in this posting
- Java
- Scala
- AWS
- Datadog
- Delta
- Docker
- PostgreSQL
- S3
- Spark
- Airflow
Source — Tool mentions in context
- Own end-to-end data quality, schema governance, retention policies, and observability across ingestion, streaming, batch, and query layers - Build highly available Java/Spring Boot services for health metric computation, data operations, and dashboard backends with idempotent consumers and fault handling - Lead design reviews, mentor engineers, investigate production incidents, and drive technical strategy with Product, QA, DevOps, and partner teams
Required Qualifications - 6-10 years hands-on backend engineering with deep expertise in Java, Spring, and Spring Boot - Production experience with Apache Cassandra: data modeling, consistency tuning, compaction strategies, cluster operations, and troubleshooting
- Own the health operations dashboard platform—design real-time data aggregation, time-series analytics, and operational dashboards for internal teams - Design and operate scalable data pipelines on Amazon EMR (Apache Spark/Scala) orchestrated with Apache Airflow for high-volume device telemetry processing - Architect and operate production Apache Cassandra clusters for operational data and time-series workloads; optimize schema, compaction strategies, and replication for dashboard query performance
- Production experience with Apache Cassandra: data modeling, consistency tuning, compaction strategies, cluster operations, and troubleshooting - Strong Apache Spark and Scala experience for distributed batch processing; proven ability to run Spark jobs on Amazon EMR with Apache Airflow - Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization
- Strong PostgreSQL background and understanding of polyglot data architectures - Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch - Solid understanding of distributed systems: retries, idempotency, fault tolerance, eventual consistency
- CI/CD and production operations (Jenkins, Docker, Sentry) - Observability platforms (Datadog, Splunk) - AI-assisted development tools (Claude, Cursor, GitHub Copilot)
- Production Cassandra operations: capacity planning, monitoring, disaster recovery - Data lakehouse or warehouse patterns (Iceberg, Delta Lake) - CI/CD and production operations (Jenkins, Docker, Sentry)
- Data lakehouse or warehouse patterns (Iceberg, Delta Lake) - CI/CD and production operations (Jenkins, Docker, Sentry) - Observability platforms (Datadog, Splunk)
- Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization - Strong PostgreSQL background and understanding of polyglot data architectures - Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 14, 2026 · 4d ago
- Recorded sightings
- 2
- Last seen by us
- Oct 17, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Job description
Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.
About the Role
- Lead architecture and development of cloud data infrastructure supporting real-time health operations dashboards and telematics analytics
- Own the health operations dashboard platform—design real-time data aggregation, time-series analytics, and operational dashboards for internal teams
- Design and operate scalable data pipelines on Amazon EMR (Apache Spark/Scala) orchestrated with Apache Airflow for high-volume device telemetry processing
- Architect and operate production Apache Cassandra clusters for operational data and time-series workloads; optimize schema, compaction strategies, and replication for dashboard query performance
- Design streaming pipelines on Amazon Kinesis and Apache Flink for real-time health event processing, status aggregation, and operational alerting
- Own end-to-end data quality, schema governance, retention policies, and observability across ingestion, streaming, batch, and query layers
- Build highly available Java/Spring Boot services for health metric computation, data operations, and dashboard backends with idempotent consumers and fault handling
- Lead design reviews, mentor engineers, investigate production incidents, and drive technical strategy with Product, QA, DevOps, and partner teams
Required Qualifications
- 6-10 years hands-on backend engineering with deep expertise in Java, Spring, and Spring Boot
- Production experience with Apache Cassandra: data modeling, consistency tuning, compaction strategies, cluster operations, and troubleshooting
- Strong Apache Spark and Scala experience for distributed batch processing; proven ability to run Spark jobs on Amazon EMR with Apache Airflow
- Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization
- Strong PostgreSQL background and understanding of polyglot data architectures
- Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch
- Solid understanding of distributed systems: retries, idempotency, fault tolerance, eventual consistency
- Experience with real-time analytics systems or operational dashboards
- Ability to debug complex production issues across services, jobs, and data stores; experience mentoring engineers
Preferred Qualifications
- Production Cassandra operations: capacity planning, monitoring, disaster recovery
- Data lakehouse or warehouse patterns (Iceberg, Delta Lake)
- CI/CD and production operations (Jenkins, Docker, Sentry)
- Observability platforms (Datadog, Splunk)
- AI-assisted development tools (Claude, Cursor, GitHub Copilot)
Education
- B.Tech/M.Tech in Computer Science, Engineering, or related field; or equivalent professional experience
We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.
If there is a match between your experiences/skills and the Company's needs, we will contact you directly.
Netradyne is an equal-opportunity employer.
Applicants only - Recruiting agencies do not contact.
Recruitment Fraud Alert!
There has been an increase in fraud that targets job seekers. Scammers may present themselves to job seekers as Netradyne employees or recruiters. Please be aware that Netradyne does not request sensitive personal data from applicants via text/instant message or any unsecured method; does not promise any advance payment for work equipment set-up and does not use recruitment or job-sourcing agencies that charge candidates an advance fee of any kind. Official communication about your application will only come from emails ending in ‘@netradyne.com’ or ‘@us-greenhouse-mail.io’.
Please review and apply to our available job openings at Netradyne.com/company/careers. For more information on avoiding and reporting scams, please visit the Federal Trade Commission's job scams website.
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- Ask the employer about the salary range before committing time to the process.
Complete your application on www.netradyne.com. The employer’s form will show what is required.
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bengaluru, Karnataka, India
Working pattern and location restrictions need checking in the full posting.
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