Equifax – Product Support Analyst

Job Description

The Equifax Product Support Analyst role in Pune is an excellent opportunity for technology professionals who are interested in cloud platforms, data processing, production support, and large-scale data delivery systems. Working as part of the Technical Fulfillment team, the Product Support Analyst will help configure, operate, monitor, and troubleshoot a high-volume batch data delivery platform built on Google Cloud Platform (GCP). The position involves working with sophisticated data processing workflows where accuracy, reliability, and timely execution are essential. Candidates will be responsible for configuring data delivery processes according to established procedures and client requirements, monitoring scheduled jobs, validating processed data, and investigating issues that could affect successful delivery. This makes the position particularly suitable for candidates who enjoy analytical problem-solving and want practical exposure to cloud computing, data engineering operations, workflow orchestration, and enterprise technology environments.

A major part of the role involves working with Apache Airflow, configuration files, data pipelines, cloud infrastructure, and automated processing workflows. The Product Support Analyst will deploy and manage Airflow DAGs, use standardized DAG templates, monitor pipeline execution, and diagnose configuration, scheduling, and dependency-related problems. The role also requires careful data quality validation because Equifax handles information that can directly influence important financial and business decisions. Analysts will therefore need to pay close attention to data integrity, file formats, encoding standards, APIs, security requirements, and deployment procedures. Familiarity with technologies such as Google Cloud Storage, BigQuery, Dataflow, Cloud Composer, Google Cloud Monitoring, and Cloud Logging can provide an advantage. Basic scripting knowledge, particularly Python or shell scripting, can further help analysts automate repetitive tasks and investigate technical problems more efficiently.

Beyond technical platform operations, this position has a strong focus on client service, ownership, collaboration, and continuous improvement. Product Support Analysts work with Engineering, Data Operations, and other internal teams to investigate fulfillment issues and improve the reliability of data delivery processes. They may also assist with production incidents, validate fixes in higher environments, maintain configuration records, and contribute to technical documentation and knowledge-base articles. Following SDLC practices, security controls, and data privacy standards is an important part of every configuration or deployment activity. The role offers exposure to a modern cloud-native technology environment while developing valuable skills in production support, data operations, cloud monitoring, incident management, and workflow automation. For professionals looking to build a career around Google Cloud, data platforms, technical support, or cloud operations, this Equifax opportunity can provide a strong foundation and meaningful enterprise-level experience.

Roles & Responsibilities

1. Configure Data Processing Workflows
   Configure and execute batch data processing workflows according to established procedures, technical requirements, and individual client specifications while maintaining accuracy throughout the delivery process.
2. Manage Airflow Pipelines
   Deploy, operate, and monitor complex data pipelines orchestrated through Apache Airflow, ensuring workflows execute according to their defined schedules and dependencies.
3. Use Standard DAG Templates
   Leverage standardized Airflow DAG templates and extend them when required to maintain consistency, simplify deployments, and support faster implementation across different environments.
4. Monitor Production Jobs
   Continuously monitor data processing jobs and identify failures, delays, unexpected behavior, or dependency problems that could affect successful and timely data delivery.
5. Perform Data Validation
   Conduct data quality checks and validation activities to confirm that processed information is complete, accurate, correctly formatted, and suitable for delivery to clients.
6. Troubleshoot Cloud Issues
   Investigate complex configuration, scheduling, dependency, and infrastructure problems within GCP and associated systems, escalating issues appropriately when additional engineering support is required.
7. Maintain Security Standards
   Follow established information-security, privacy, and access-control procedures when working with configurations, financial data, cloud services, and client-related information.
8. Follow SDLC Procedures
   Apply Software Development Life Cycle practices when making configuration changes, deploying updates, testing modifications, or introducing improvements to existing workflows.
9. Support Client Fulfillment
   Help investigate and resolve fulfillment-related concerns, understanding that accurate and timely data delivery directly influences client satisfaction, trust, and business operations.
10. Collaborate Across Teams
    Work closely with Engineering, Data Operations, and other technical teams to investigate incidents, resolve delivery problems, improve workflows, and strengthen platform reliability.
11. Maintain Technical Documentation
    Keep configuration records, operational procedures, troubleshooting information, and knowledge-base articles accurate and up to date for future reference and team support.
12. Identify Automation Opportunities
    Look for repetitive or inefficient configuration and support activities that could be improved through scripting, automation, standardized workflows, or process enhancements.

Requirements & Eligibility

1. Educational Qualification
   Candidates should have a bachelor's degree in Computer Science, Information Technology, Software Engineering, or an equivalent technical discipline.
2. Analytical Problem Solving
   Strong analytical thinking and a structured approach to troubleshooting are important because the role involves identifying the root causes of pipeline, configuration, scheduling, and data-processing issues.
3. Data Processing Knowledge
   Candidates should understand basic data-processing concepts, batch processing workflows, file-based data delivery, dependencies, and the importance of maintaining data accuracy.
4. Configuration File Experience
   Familiarity with configuration files such as YAML is beneficial, particularly for understanding and modifying application, pipeline, or cloud-service configurations.
5. Cloud Computing Fundamentals
   A basic understanding of cloud computing concepts is expected. Exposure to Google Cloud Platform (GCP) can provide an additional advantage.
6. File Encoding Knowledge
   Candidates should be comfortable working with different file formats and encoding standards and understand how encoding problems can affect data processing and delivery.
7. API Testing Knowledge
   Familiarity with API testing tools and the ability to understand data interfaces can help when validating integrations and troubleshooting data delivery problems.
8. Scripting Skills
   Basic shell scripting knowledge is useful for operational tasks, troubleshooting, and automation. Experience with Python is an added advantage.
9. Cloud Platform Skills
   Knowledge of GCP services such as Cloud Storage, BigQuery, Dataflow, or Cloud Composer can strengthen a candidate's profile and help with day-to-day platform operations.
10. Monitoring & Communication
    Candidates should be comfortable using monitoring and logging tools, communicating technical issues clearly, working with cross-functional teams, and taking ownership of assigned operational problems.

Preferred Skills

Candidates with additional experience in the following areas may have an advantage:

• Google Cloud Platform and cloud-native technologies
• Apache Airflow and Airflow DAG management
• Google Cloud Composer
• Google Cloud Storage
• BigQuery and Dataflow
• Google Cloud Logging and Monitoring
• Python or shell scripting
• Java or other object-oriented programming languages
• API testing and data-interface validation
• YAML and configuration management
• Production support and incident management
• Data quality and batch-processing systems
• SDLC and deployment practices
• Technical documentation and knowledge management

Expected Salary

For a Product Support Analyst in Pune, a reasonable market-oriented estimate is approximately ₹4.5 lakh to ₹8 lakh per year, depending on experience, technical skills, cloud exposure, and the candidate's overall profile. Professionals with practical experience in GCP, Apache Airflow, Python, data operations, production support, or cloud monitoring may command compensation toward the higher end of the range.

Why Join Equifax?

Equifax provides an opportunity to work in an environment where data, analytics, cloud technology, and financial information systems come together to support important business decisions. The Product Support Analyst position offers hands-on exposure to Google Cloud, data pipelines, Airflow orchestration, production operations, and enterprise-scale data delivery.

The company also emphasizes professional development, learning opportunities, career growth, collaboration, and an inclusive workplace. The Pune role follows a hybrid working model and offers benefits that can support both professional development and long-term career progression. For technology professionals interested in cloud operations and data platforms, the role can provide valuable experience working with mission-critical systems and cross-functional engineering teams.

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