Senior Big Data Engineer

Qualys • Bachelor's Degree • Java • Python • Scala • 27 days ago
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≈ $28k – $56k per year (Estimated)
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In office (Pune)
Seniority
Senior · 5+ years exp
Employment
Full-Time
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Qualys

Qualys, Inc. is a publicly traded enterprise cybersecurity, compliance, and IT solutions provider headquartered in Foster City, California. Founded in 1999 as a pioneer in SaaS-delivered vulnerability management, the company provides the Qualys Enterprise TruRisk Platform. Its single-agent cloud architecture unifies cybersecurity asset management, vulnerability management detection and response (VMDR), patch management, web application security, policy compliance, and cloud security across hybrid IT environments, public clouds, and containers.
qualys.com • HQ: Foster City, United States • Information Security • Endpoint Security • Cybersecurity • 1001-5000 employees • Est. 1999

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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