📍 Job Overview

Job Title: Staff Software Development Engineer (Cloud Observability)
Company: Zscaler
Location: Bengaluru, Karnataka, India
Job Type: Hybrid
Category: DevOps Engineer
Date Posted: July 23, 2025
Experience Level: 5-10 years
Remote Status: On-site/Hybrid

🚀 Role Summary

Design, build, and scale Zscaler's cloud data analytics platform, processing terabytes of endpoint telemetry.
Engineer and maintain a scalable alerting and incident detection engine using Python and workflow orchestrators.
Create and manage insightful Grafana dashboards for system health and performance, benefiting engineering, support, and leadership teams.
Optimize the data platform for cost, performance, and reliability, owning the architecture and mentoring other engineers.

📝 Enhancement Note: This role requires a strong background in data engineering, with a focus on large-scale data processing and cloud computing. Familiarity with Zscaler's current tech stack, including Azure Data Explorer (ADX), Grafana, and Apache Airflow, would be highly beneficial.

💻 Primary Responsibilities

Platform Development: Design, build, and scale the cloud data analytics platform, ensuring efficient ingestion, processing, and querying of terabytes of endpoint telemetry.
Alerting & Incident Detection: Engineer and maintain a scalable alerting engine using Python and workflow orchestrators, enabling timely incident detection and resolution.
Data Visualization: Create and manage insightful Grafana dashboards, providing clear, actionable views of the system's health and performance for various stakeholders.
Platform Optimization: Optimize the data platform for cost, performance, and reliability, ensuring the system is robust, enhanceable, and meets the needs of the entire team.
Mentoring & Collaboration: Own the architecture, mentor other engineers, and collaborate with cross-functional teams to build and maintain a high-performing, reliable data platform.

📝 Enhancement Note: This role requires a strong focus on data processing, automation, and building data pipelines. Experience with infrastructure as code (IaC) tools like Terraform or Bicep would be advantageous for platform optimization and cost management.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may be considered in lieu of a degree.

Experience: 5+ years of professional experience in a data engineering, backend, or SRE role with a focus on large-scale data.

Required Skills:

Expert-level proficiency in SQL or Kusto Query Language (KQL)
Strong programming skills in Python, with a focus on data processing, automation, and building data pipelines
Hands-on experience with at least one major cloud provider, with Azure being highly preferred
Demonstrated experience building and managing systems for big data analytics, time-series monitoring, alerting/anomaly detection, or data visualization

Preferred Skills:

Direct experience with Zscaler's current tech stack: Azure Data Explorer (ADX), Grafana, and Apache Airflow
Familiarity with infrastructure as code (IaC) tools like Terraform or Bicep

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate expertise in data processing, automation, and building data pipelines through relevant projects in your portfolio.
Showcase your ability to create and manage insightful dashboards using tools like Grafana, highlighting your data visualization skills.
Highlight your experience with cloud computing, big data analytics, and monitoring systems, with a focus on large-scale data processing.

Technical Documentation:

Provide clear, well-commented code samples showcasing your proficiency in Python and your chosen query language (SQL or KQL).
Include case studies or project documentation demonstrating your experience with data analytics, alerting systems, and data visualization.
Highlight any relevant certifications or training in data engineering, cloud computing, or related fields.

📝 Enhancement Note: To stand out, tailor your portfolio to highlight your experience with Zscaler's preferred tech stack and demonstrate your ability to optimize data platforms for cost, performance, and reliability.

💵 Compensation & Benefits

Salary Range: INR 2,000,000 - 3,500,000 per annum (Estimated based on industry standards for senior data engineering roles in Bengaluru)

Benefits:

Various health plans
Time off plans for vacation and sick time
Parental leave options
Retirement options
Education reimbursement
In-office perks, and more!

Working Hours: Full-time (40 hours/week), with flexible hours for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: The estimated salary range is based on market research for senior data engineering roles in Bengaluru. Zscaler offers a comprehensive benefits package, including various health plans, time off plans, parental leave options, retirement options, education reimbursement, and in-office perks.

🎯 Team & Company Context

🏢 Company Culture

Industry: Zscaler operates in the cybersecurity industry, focusing on cloud-based security solutions for enterprise customers.

Company Size: Zscaler is a mid-sized company with a global presence, employing around 2,000 people worldwide.

Founded: 2007

Team Structure:

The Shared Platform Services team is responsible for building and maintaining the cloud data analytics platform, alerting systems, and data visualization tools.
The team consists of data engineers, backend engineers, SREs, and data analysts, working collaboratively to ensure the platform's reliability, performance, and scalability.
The team reports to the Director of Software Engineering and works closely with cross-functional teams, including engineering, support, and leadership.

Development Methodology:

Zscaler follows Agile methodologies, with a focus on iterative development, continuous integration, and continuous deployment (CI/CD).
The team uses tools like Jira, Confluence, and Git for project management, collaboration, and version control.
Zscaler emphasizes code reviews, testing, and quality assurance to ensure the reliability and performance of its products.

Company Website: Zscaler

📝 Enhancement Note: Zscaler's company culture values innovation, collaboration, and a customer-centric approach. The company fosters an inclusive environment that supports the growth and development of its employees.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the senior level, focusing on designing, building, and optimizing large-scale data platforms. The ideal candidate will have extensive experience in data engineering, with a strong background in cloud computing, big data analytics, and monitoring systems.

Reporting Structure: The Staff Software Development Engineer reports directly to the Director of Software Engineering and works collaboratively with cross-functional teams, including engineering, support, and leadership.

Technical Impact: The role has a significant impact on Zscaler's cloud data analytics platform, alerting systems, and data visualization tools. The ideal candidate will be responsible for designing and implementing scalable, reliable, and cost-effective solutions that meet the needs of the entire team.

Growth Opportunities:

Technical Growth: Zscaler offers opportunities for technical growth, including mentorship, training, and involvement in emerging technologies.
Leadership Development: With experience and strong performance, there may be opportunities to move into technical leadership roles, managing teams and driving architectural decisions.
Career Progression: As a senior-level role, this position offers opportunities for career progression within Zscaler's data engineering and cloud computing teams.

📝 Enhancement Note: Zscaler's career growth opportunities are tailored to the individual's skills, interests, and career goals. The company encourages continuous learning and supports employees in pursuing relevant certifications and training.

🌐 Work Environment

Office Type: Zscaler's office in Bengaluru is a modern, collaborative workspace designed to foster innovation and teamwork.

Office Location(s): Bengaluru, Karnataka, India

Workspace Context:

Zscaler provides its employees with state-of-the-art equipment, including multiple monitors and testing devices, to ensure optimal productivity.
The workspace is designed to encourage collaboration, with open-plan offices and dedicated team spaces.
Zscaler offers flexible work arrangements, with hybrid and remote work options available for eligible roles.

Work Schedule: Full-time (40 hours/week), with flexible hours for deployment windows, maintenance, and project deadlines. Zscaler offers a hybrid work arrangement, with employees expected to work on-site for a minimum of two days per week.

📝 Enhancement Note: Zscaler's work environment prioritizes collaboration, innovation, and employee well-being. The company offers flexible work arrangements to support work-life balance and employee satisfaction.

📄 Application & Technical Interview Process

Interview Process:

Online Assessment: A technical assessment focusing on data processing, automation, and building data pipelines using Python and your chosen query language (SQL or KQL).
Technical Deep Dive: A detailed discussion of your experience with cloud computing, big data analytics, and monitoring systems, with a focus on large-scale data processing.
Behavioral & Cultural Fit: An assessment of your problem-solving skills, communication, and cultural fit with Zscaler's values and team dynamics.
Final Review: A review of your portfolio, technical skills, and overall fit for the role by the hiring manager and other stakeholders.

Portfolio Review Tips:

Highlight your experience with cloud computing, big data analytics, and monitoring systems through relevant projects and case studies.
Demonstrate your ability to create and manage insightful dashboards using tools like Grafana, showcasing your data visualization skills.
Include clear, well-commented code samples showcasing your proficiency in Python and your chosen query language (SQL or KQL).

Technical Challenge Preparation:

Brush up on your Python skills, with a focus on data processing, automation, and building data pipelines.
Familiarize yourself with Zscaler's preferred tech stack, including Azure Data Explorer (ADX), Grafana, and Apache Airflow.
Prepare for questions about cloud computing, big data analytics, and monitoring systems, with a focus on large-scale data processing.

ATS Keywords: [Provided in the "Technology Stack & Web Infrastructure" section below]

📝 Enhancement Note: Zscaler's interview process is designed to assess your technical skills, problem-solving abilities, and cultural fit with the company's values and team dynamics. The company prioritizes a fair, transparent, and inclusive hiring process.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: (Not applicable for this role)

Backend & Server Technologies:

Azure Data Explorer (ADX): Zscaler's preferred data analytics platform for ingesting, processing, and querying terabytes of endpoint telemetry.
Apache Airflow: Zscaler uses Apache Airflow for workflow orchestration, automating data processing and deployment pipelines.
Python: The primary programming language used for data processing, automation, and building data pipelines at Zscaler.

Development & DevOps Tools:

Grafana: Zscaler uses Grafana for data visualization, creating insightful dashboards that provide clear, actionable views of the system's health and performance.
Terraform/Bicep: Zscaler uses infrastructure as code (IaC) tools like Terraform or Bicep for managing and provisioning cloud resources, ensuring cost optimization and reliability.
Git: Zscaler uses Git for version control, enabling collaborative development and code reviews.

ATS Keywords:

Programming Languages: Python, SQL, KQL
Cloud Providers: Azure
Data Analytics Platforms: Azure Data Explorer (ADX), Apache Airflow
Data Visualization Tools: Grafana
Infrastructure as Code (IaC) Tools: Terraform, Bicep
Version Control Systems: Git
Web Development Frameworks: (Not applicable for this role)
Server Technologies: (Not applicable for this role)
Databases: (Not applicable for this role)
Soft Skills: Problem-solving, communication, collaboration, innovation, adaptability
Industry Terms: Data engineering, backend development, SRE, cloud computing, big data analytics, monitoring systems, alerting, anomaly detection, data visualization

📝 Enhancement Note: Zscaler's technology stack is designed to support large-scale data processing, cloud computing, and monitoring systems. Familiarity with the company's preferred tech stack, including Azure Data Explorer (ADX), Grafana, and Apache Airflow, would be highly beneficial for this role.

👥 Team Culture & Values

Web Development Values:

Innovation: Zscaler values innovation and encourages its employees to think creatively and challenge the status quo.
Customer-centric: Zscaler prioritizes the needs of its customers, ensuring its products and services meet their evolving requirements.
Collaboration: Zscaler fosters a collaborative work environment, encouraging teamwork and knowledge sharing.
Continuous Learning: Zscaler supports its employees' professional development, offering mentorship, training, and opportunities to work with emerging technologies.

Collaboration Style:

Cross-functional Integration: Zscaler encourages collaboration between its data engineering, backend engineering, SRE, and data analyst teams, as well as with other departments, including engineering, support, and leadership.
Code Review Culture: Zscaler prioritizes code reviews, ensuring the quality, performance, and maintainability of its products.
Knowledge Sharing: Zscaler fosters a culture of knowledge sharing, with regular team meetings, workshops, and training sessions.

📝 Enhancement Note: Zscaler's team culture values innovation, collaboration, and continuous learning. The company encourages its employees to think creatively, work collaboratively, and pursue professional development opportunities.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Large-scale Data Processing: Design, build, and optimize data pipelines to efficiently process terabytes of endpoint telemetry.
Cost Optimization: Ensure the data platform's cost-effectiveness while maintaining performance and reliability.
Scalability & Performance: Design and implement scalable, high-performing data processing and alerting systems that meet the needs of the entire team.
Emerging Technologies: Stay up-to-date with emerging technologies in data engineering, cloud computing, and monitoring systems, and evaluate their potential integration into Zscaler's products.

Learning & Development Opportunities:

Technical Skill Development: Zscaler offers opportunities for technical skill development, including mentorship, training, and involvement in emerging technologies.
Career Progression: With experience and strong performance, there may be opportunities to move into technical leadership roles, managing teams and driving architectural decisions.
Community Involvement: Zscaler encourages its employees to participate in relevant industry events, conferences, and online communities, fostering a culture of continuous learning and collaboration.

📝 Enhancement Note: Zscaler's technical challenges and learning opportunities are tailored to the individual's skills, interests, and career goals. The company encourages continuous learning and supports employees in pursuing relevant certifications and training.

💡 Interview Preparation

Technical Questions:

Data Processing & Automation: Questions focusing on your experience with data processing, automation, and building data pipelines using Python and your chosen query language (SQL or KQL).
Cloud Computing: Questions assessing your understanding of cloud computing concepts, with a focus on Azure and Zscaler's preferred tech stack.
Big Data Analytics & Monitoring Systems: Questions evaluating your experience with big data analytics, monitoring systems, and alerting/anomaly detection.
Data Visualization: Questions exploring your ability to create and manage insightful dashboards using tools like Grafana.

Company & Culture Questions:

Zscaler's Values: Questions assessing your understanding of Zscaler's values, including innovation, customer-centricity, collaboration, and continuous learning.
Team Dynamics: Questions evaluating your ability to work collaboratively with cross-functional teams, including data engineers, backend engineers, SREs, and data analysts.
Problem-solving: Questions focusing on your problem-solving skills, communication, and adaptability in a dynamic work environment.

Portfolio Presentation Strategy:

Data Processing & Automation: Highlight your experience with data processing, automation, and building data pipelines through relevant projects and case studies.
Cloud Computing: Demonstrate your understanding of cloud computing concepts, with a focus on Azure and Zscaler's preferred tech stack.
Big Data Analytics & Monitoring Systems: Showcase your experience with big data analytics, monitoring systems, and alerting/anomaly detection through relevant projects and case studies.
Data Visualization: Present your ability to create and manage insightful dashboards using tools like Grafana, highlighting your data visualization skills.

📝 Enhancement Note: Zscaler's interview preparation focuses on assessing your technical skills, problem-solving abilities, and cultural fit with the company's values and team dynamics. The company prioritizes a fair, transparent, and inclusive hiring process.

📌 Application Steps

To apply for this Staff Software Development Engineer (Cloud Observability) position at Zscaler:

Submit Your Application: Click the application link provided in the job listing and submit your resume, highlighting your relevant experience in data engineering, backend development, or SRE roles.
Prepare Your Portfolio: Tailor your portfolio to showcase your experience with cloud computing, big data analytics, and monitoring systems, with a focus on large-scale data processing and data visualization. Include clear, well-commented code samples showcasing your proficiency in Python and your chosen query language (SQL or KQL).
Brush Up on Your Technical Skills: Review your knowledge of Python, cloud computing, big data analytics, and monitoring systems, with a focus on Zscaler's preferred tech stack, including Azure Data Explorer (ADX), Grafana, and Apache Airflow.
Research Zscaler: Familiarize yourself with Zscaler's company culture, values, and team dynamics. Prepare for questions about your understanding of the company and your fit within its collaborative, innovative work environment.

📝 Enhancement Note: Zscaler's application process is designed to assess your technical skills, problem-solving abilities, and cultural fit with the company's values and team dynamics. The company prioritizes a fair, transparent, and inclusive hiring process.

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

Tailor every section specifically to data engineering, backend development, and SRE roles, with a focus on large-scale data processing and cloud computing.
Include data processing, automation, and building data pipelines as core responsibilities.
Emphasize cloud computing, big data analytics, and monitoring systems in skills and qualifications.
Address data visualization and alerting/anomaly detection in primary responsibilities and portfolio requirements.
Highlight Zscaler's preferred tech stack, including Azure Data Explorer (ADX), Grafana, and Apache Airflow, in technology stack and interview preparation sections.

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information.
Only include Enhancement Notes when making significant inferences about technical responsibilities, with specific reasoning based on role level and data engineering industry practices.
Be comprehensive but concise, prioritizing actionable information over descriptive text.
Strategically distribute data engineering and cloud computing-related keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and data engineering specialization.

Industry Expertise:

Include specific data engineering, backend development, and SRE technologies, frameworks, and infrastructure tools relevant to the role.
Address data engineering career progression paths and technical leadership opportunities in data engineering teams.
Provide tactical advice for data portfolio development, live demonstrations, and project case studies.
Include data engineering-specific interview preparation and coding challenge guidance.
Emphasize data processing, automation, and building data pipelines in primary responsibilities and skills qualifications.
Highlight cloud computing, big data analytics, and monitoring systems in role analysis, company context, and team culture sections.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use data engineering and cloud computing industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to data engineering professionals.
Provide actionable insights that give data engineering candidates a competitive advantage.
Focus on data engineering team culture, cross-functional collaboration, and user impact measurement.

Technical Focus & Portfolio Emphasis:

Emphasize data processing, automation, and building data pipelines in primary responsibilities and skills qualifications.
Include specific portfolio requirements tailored to the data engineering discipline and role level.
Address browser compatibility, accessibility standards, and user experience design principles in data visualization portfolio requirements.
Focus on problem-solving methods, performance optimization, and scalable data architecture in primary responsibilities and skills qualifications.
Include technical presentation skills and stakeholder communication for data projects.

Avoid:

Generic business jargon not relevant to data engineering or cloud computing roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific data engineering role.
Marketing language unrelated to data engineering, backend development, or SRE disciplines.

Generate comprehensive, data engineering-focused content that serves as a valuable resource for data engineering, backend development, and SRE professionals seeking their next opportunity.

Staff Software Development Engineer(Cloud Observability)