Senior Big Data Engineer
Pune
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingDesign, build, and maintain high-throughput data platform and pipeline components using Spark and Kafka.
Collaborate with product, professional services, and sales engineering teams on architecture design and technical trade-offs.
Mentor junior and mid-level engineers on complex technical issues and pipeline performance.
From the employer’s posting
Responsibilities: Design, build, and maintain high-throughput data platform and pipeline components using Spark and Kafka. Debug, tune, and optimize Spark jobs and Kafka pipelines to manage growing data volumes.
Debug, tune, and optimize Spark jobs and Kafka pipelines to manage growing data volumes. Collaborate with product, professional services, and sales engineering teams on architecture design and technical trade-offs. Establish and refine technical standards, system documentation, and best practices across the engineering team.
Establish and refine technical standards, system documentation, and best practices across the engineering team. Mentor junior and mid-level engineers on complex technical issues and pipeline performance. Required Qualifications:
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
- Demonstrated experience designing, building, and optimizing distributed pipelines using Apache Spark and Apache Kafka.
- Hands-on experience scaling data platform infrastructure to process high-volume/high-throughput transaction workloads.
Preferred experience
- Experience working with high-volume, multi-tenant enterprise platform environments.
- Proficiency in Scala, Java, or Python for data processing applications.
- Proven experience mentoring junior or mid-level engineering team members.
Qualification wording
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
Demonstrated experience designing, building, and optimizing distributed pipelines using Apache Spark and Apache Kafka.
Hands-on experience scaling data platform infrastructure to process high-volume/high-throughput transaction workloads.
Experience working with high-volume, multi-tenant enterprise platform environments.
Proficiency in Scala, Java, or Python for data processing applications.
Proven experience mentoring junior or mid-level engineering team members.
Tools in this posting
- Java
- Python
- Scala
- Kafka
- Spark
Source — Tool mentions in context
- Experience working with high-volume, multi-tenant enterprise platform environments. - Proficiency in Scala, Java, or Python for data processing applications. - Proven experience mentoring junior or mid-level engineering team members.
Responsibilities: - Design, build, and maintain high-throughput data platform and pipeline components using Spark and Kafka. - Debug, tune, and optimize Spark jobs and Kafka pipelines to manage growing data volumes.
- Design, build, and maintain high-throughput data platform and pipeline components using Spark and Kafka. - Debug, tune, and optimize Spark jobs and Kafka pipelines to manage growing data volumes. - Collaborate with product, professional services, and sales engineering teams on architecture design and technical trade-offs.
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical field. - Demonstrated experience designing, building, and optimizing distributed pipelines using Apache Spark and Apache Kafka. - Hands-on experience scaling data platform infrastructure to process high-volume/high-throughput transaction workloads.
Job description
Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
Senior Big Data Engineer
Job Description: We are seeking a Senior Big Data Engineer to design, build, and operate core components of the data platform and pipeline architecture behind Qualys' Enterprise TruRisk Platform, processing billions of daily transactions.
Responsibilities:
- Design, build, and maintain high-throughput data platform and pipeline components using Spark and Kafka.
- Debug, tune, and optimize Spark jobs and Kafka pipelines to manage growing data volumes.
- Collaborate with product, professional services, and sales engineering teams on architecture design and technical trade-offs.
- Establish and refine technical standards, system documentation, and best practices across the engineering team.
- Mentor junior and mid-level engineers on complex technical issues and pipeline performance.
Required Qualifications:
- Minimum 5 years of experience in data engineering or big data platform development.
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
- Demonstrated experience designing, building, and optimizing distributed pipelines using Apache Spark and Apache Kafka.
- Hands-on experience scaling data platform infrastructure to process high-volume/high-throughput transaction workloads.
Preferred Qualifications:
- Experience working with high-volume, multi-tenant enterprise platform environments.
- Proficiency in Scala, Java, or Python for data processing applications.
- Proven experience mentoring junior or mid-level engineering team members.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on qualys.wd5.myworkdayjobs.com. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
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- Location & working pattern
Pune
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- Status in our records
- Active
- First seen by us
- Aug 6, 2026
- Recorded sightings
- 2
- Last seen by us
- Sep 29, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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