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Senior Big Data Engineer

Qualys • Cybersecurity • Endpoint Security • Bachelor's Degree • Python • Java • Scala • 2 months ago

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Salary

≈ $21k – $42k per year (Estimated)

Location

In office (Pune)

Seniority

Senior · 5+ years exp

Employment

Full-Time

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Aug 5, 2026.

Overview

Company

Impact

Profile match

Qualys

Qualys is an American security company founded in 1999 that pioneered delivering vulnerability scanning as a cloud service rather than as software customers installed and ran themselves. Its platform builds an inventory of an organisation's assets, scans them for vulnerabilities and misconfigurations, prioritises what to fix based on whether an exploit exists and is being used, and increasingly handles the patching itself. Headquartered in Foster City and listed on Nasdaq, it competes with Tenable and Rapid7 and has extended into cloud security posture management and compliance reporting.

qualys.com • HQ: Foster City, United States • Security Compliance • Cloud Security • Vulnerability Management • 1001-5000 employees • Est. 1999

Tech stack of Qualys

Backed by Bessemer Venture Partners

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.

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