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Staff Data Automation Engineer - job 1 of 3

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce.   We operate the world’s most sophisticated processing networks capable of handling more than 65k secure transactions a second across 80M merchants, 15k Financial Institutions, and billions of everyday people.   While working with us you’ll get to work on complex distributed systems and solve massive scale problems centered on new payment flows, business and data solutions, cyber security, and B2C platforms.     

The Opportunity: 

We are looking for Versatile, curious, and energetic Software Engineers who embrace solving complex challenges on a global scale.  As a Visa Software Engineer, you will be an integral part of a multi-functional development team inventing, designing, building, and testing software products that reach a truly global customer base. While building components of powerful payment technology, you will get to see your efforts shaping the digital future of monetary transactions. 

The Work Itself:

Engineer data systems and pipelines that handle vast datasets influencing Visa’s internal standards for data scalability, security, and reusability.
Collaborate across multiple teams to create design artifacts and develop best-in-class data solutions for Visa’s diverse technical offerings.
Actively contribute to data quality improvements, valuable service technology, and new business flows in diverse agile squads.
Develop robust and scalable data products intended for various stakeholders, including end-user merchants, B2B, and business-to-government solutions.
Leverage innovative technologies to build the next generation of payment services, transaction platforms, real-time analytics, and data-driven insights.
Opportunities to make a difference on a global or local scale through mentorship and continued learning opportunities.
Essential Functions:

Demonstrates relevant technical working knowledge to understand data requirements and architectural decisions.
Identifies and contributes to solution strategies that improve the design and functionality of data pipelines and processing frameworks, under minimal guidance.
Applies standard processes on the use of programming languages and tools (e.g., java, Scala, Python, SQL, Spark) to develop and optimize data workflows.
Collaborates with others to support the piloting of new data capabilities and features that enhance analytics and reporting across e-commerce products.
Analyzes data anomalies for simple issues and applies debugging tools to verify assumptions and improve data integrity.
The Skills You Bring:

Energy and Experience: A growth mindset that is curious and passionate about data technologies and enjoys challenging projects on a global scale.
Challenge the Status Quo: Comfort in pushing the boundaries, ‘hacking’ beyond traditional data solutions.
Language and Tool Expertise: Proficiency in one or more data processing languages and tools (e.g., Python, SQL, Spark).
Builder: Experience building and deploying modern data services and pipelines with quality and scalability.
Learner: Constant drive to learn new technologies such as Hadoop, Kafka, Kubernetes, Docker, etc.
Partnership: Experience collaborating with Product, Test, DevOps, and Agile/Scrum teams.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications
8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.

Preferred Qualifications
9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
Educational Background: Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.
Experience: 6+ years of hands-on experience in data engineering, data automation, or a related role.
Programming Skills: Proficiency in programming languages such as Python, Java, or Scala for data manipulation and automation.
Database Management: Strong experience with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).
Data Processing Frameworks: Experience with data processing frameworks such as Apache Spark, Apache Hadoop, or Apache Flink.
ETL Tools: Proficiency in ETL tools like Apache NiFi, Talend, Informatica, or Microsoft SSIS.
Data Generators and Copying: Ability to build data generators and automate data copying processes.

Batch Processing Expertise:

Extensive experience in designing, implementing, and maintaining batch processing systems.
Proficiency in scheduling and orchestrating batch jobs using tools like Apache Airflow, Control-M, or Cron jobs.
Strong understanding of batch processing principles, including job dependencies, scheduling, and error handling.
Data Automation Framework Development:

Ability to develop custom automation frameworks tailored for batch processing applications.
Experience in automating the end-to-end data pipeline, including data extraction, transformation, and loading (ETL) processes.
Creation of reusable and scalable automation scripts using Python, Bash, or other scripting languages.
Data Generators and Copy Automation:

Expertise in building and maintaining data generators for synthetic data creation to support testing and development environments.
Experience in automating data copying and replication processes across different environments and databases.
Performance Optimization:

Experience in optimizing batch jobs for performance and efficiency, including resource allocation, parallel processing, and job prioritization.
Ability to monitor and troubleshoot batch job performance issues and implement necessary improvements.
Error Handling and Recovery:

Development of robust error handling and recovery mechanisms to ensure the reliability and resilience of batch processing workflows.
Implementation of alerting and notification systems to promptly address job failures and exceptions.
Data Quality and Validation:

Implementation of automated data quality checks and validation steps within batch processes to ensure data accuracy and integrity.
Experience with tools and frameworks for automated data validation, such as Great Expectations or custom validation scripts.
Documentation and Best Practices:

Strong documentation skills to create comprehensive guides, best practices, and standard operating procedures (SOPs) for batch automation processes.
Knowledge of industry best practices for batch processing and data automation.
Tools and Technologies for Automation in Batch Applications:
Scheduling and Orchestration: Apache Airflow, Control-M, Cron
Scripting Languages: Python, Bash, Shell scripting
Data Processing Frameworks: Apache Spark, Apache Hadoop
ETL Tools: Apache NiFi, Talend
Data Quality and Validation: Great Expectations, custom validation scripts
Monitoring and Alerting: Prometheus, Grafana, custom alerting systems

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Average salary estimate

$110000 / YEARLY (est.)
min
max
$90000K
$130000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Staff Data Automation Engineer, Visa

Join Visa as a Staff Data Automation Engineer in Bangalore, India, where you’ll help shape the future of payments. At Visa, we’re on a mission to connect the world through innovative and secure payment solutions. If you’re a versatile and energetic engineer, this is a fantastic opportunity for you to work on complex data systems that handle vast datasets, influencing data scalability and security for the entire organization. You’ll collaborate with cross-functional teams to develop best-in-class data solutions while also having the chance to contribute to exciting new payment flows and analytics tools. Your work won’t just be about building components; it will be about impacting the digital landscape of monetary transactions on a global scale. You'll dive deep into programming languages like Python, SQL, and Spark to optimize data workflows and address multiple stakeholder needs, including merchants and governments. We're looking for someone who has a growth mindset, enjoys tackling challenging projects, and isn’t afraid to push the boundaries of traditional data solutions. At Visa, your contributions won’t go unnoticed; we believe in mentorship and continual learning opportunities that enable you to make a difference both locally and internationally. Ready to redefine the future of commerce? Apply now!

Frequently Asked Questions (FAQs) for Staff Data Automation Engineer Role at Visa
What are the main responsibilities of a Staff Data Automation Engineer at Visa?

As a Staff Data Automation Engineer at Visa, your main responsibilities include engineering data systems and pipelines that manage large datasets crucial for data scalability and security. You will collaborate with various teams to design innovative data solutions, improve data quality, and support the development of new business flows. Additionally, you'll be involved in analyzing data anomalies, optimizing workflows with tools like Python and SQL, and developing robust data products to serve a wide range of stakeholders.

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What qualifications are preferred for the Staff Data Automation Engineer position at Visa?

Visa prefers candidates with at least nine years of relevant work experience and a Bachelor or Master's degree in fields like Computer Science or Data Science. Experience with programming languages such as Python, Java, and Scala, as well as strong skills in SQL and NoSQL databases, are essential. Proficiency in data processing frameworks like Apache Spark and experience with ETL tools are also highly valued for this role.

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How does collaboration work as a Staff Data Automation Engineer at Visa?

Collaboration is at the heart of being a Staff Data Automation Engineer at Visa. You’ll work closely with cross-functional teams, including Product Management, QA, and DevOps, to create design artifacts and best-in-class data solutions. This teamwork approach ensures that you can leverage diverse perspectives and expertise to develop high-quality data systems that meet various stakeholder needs.

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What programming languages and tools do Staff Data Automation Engineers at Visa use?

Staff Data Automation Engineers at Visa commonly use programming languages such as Python, Java, and Scala for data manipulation and automation. In addition, knowledge of ETL tools like Apache NiFi and databases like MySQL and MongoDB is critical. Engineers also work with data processing frameworks like Apache Spark, ensuring they can handle robust and scalable data solutions.

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What learning opportunities does Visa provide for Staff Data Automation Engineers?

At Visa, continuous learning and mentorship are integral to employee development. As a Staff Data Automation Engineer, you’ll have access to various training programs, workshops, and resources designed to enhance your skills in emerging technologies such as Hadoop, Kafka, and Kubernetes. This commitment to professional growth enables you to stay ahead in the rapidly evolving tech landscape.

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Common Interview Questions for Staff Data Automation Engineer
Can you explain your experience with data automation frameworks and tools?

When answering this question, highlight specific automation frameworks you’ve worked with, such as Apache Airflow or Talend. Discuss projects where you implemented these tools and the impact they had on data processing efficiency and accuracy. Emphasize your role in developing custom automation scripts and how they improved data workflows.

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Describe a challenging data problem you faced and how you resolved it.

Use the STAR method to structure your response. First, explain the Situation and Task, then discuss the Actions you took to resolve the issue, and conclude with the Results. Emphasize your analytical skills, your approach to debugging, and any tools you used to identify and fix data anomalies.

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How do you ensure data quality in your data processing tasks?

Talk about the mechanisms you use for data validation and quality checks, such as automated scripts you might have developed. Share specific examples of data quality frameworks like Great Expectations that you've implemented and the outcomes of those enhancements.

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What strategies do you employ when building scalable data pipelines?

In your answer, reflect on best practices for scalability, such as partitioning data, optimizing code for performance, or leveraging cloud services for resource scaling. Provide examples from past experiences where your decisions led to improved pipeline performance.

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What do you consider when designing data architecture?

Discuss the essential factors such as scalability, security, and flexibility. Mention specific design patterns or principles you follow, and provide examples of projects where your architectural decisions positively impacted system performance.

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How do you keep up with the latest trends and technologies in data engineering?

Explain your commitment to professional development through attending conferences, participating in workshops, and following industry blogs or forums. Sharing specific resources or communities that you engage with can showcase your dedication to staying current in the field.

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Can you describe your experience with batch processing systems?

Detail your background in designing and implementing batch processing systems, including tools you’ve used like Apache Airflow or Control-M. Discuss specific challenges you faced, the solutions you implemented, and the results for the project.

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What role do you believe collaboration plays in successful data engineering projects?

Reflect on the importance of cross-functional collaboration, sharing specific instances where teamwork led to innovation or solution enhancement. Discuss your communication and collaboration strategies that help bridge gaps between teams.

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How do you approach debugging and resolving data pipeline issues?

Discuss your systematic approach to debugging, including your methodologies for identifying bugs, tools you utilize for monitoring, and collaborative strategies for resolving issues efficiently. This shows your analytical skills and problem-solving mindset.

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What experience do you have with real-time data processing?

Talk about your experience with technologies used for real-time data processing, such as Kafka or Apache Flink. Share examples of projects where you implemented such solutions and the benefits they brought, focusing on performance improvements and user experience.

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Visa Inc. operates as a payments technology company worldwide. The company facilitates commerce through the transfer of value and information among consumers, merchants, financial institutions, businesses, strategic partners, and government entiti...

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Full-time, hybrid
DATE POSTED
April 9, 2025

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