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Staff Data Engineer - job 0 of 50

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

The Staff Data Engineer role involves leading and mentoring a team of data engineers, coordinating with other teams to manage and prioritize projects, and driving the strategy, roadmap, and execution of key data engineering initiatives. The role requires understanding and translating business needs into data models, creating robust data pipelines, and developing and maintaining data lakes. It also involves implementing and maintaining CI/CD pipelines for data solutions. The candidate should be able to define and manage data load procedures, implement data strategies, and ensure robust operational data management systems. Collaborating with stakeholders across the organization to understand their data needs and deliver solutions is also a key part of this role. The ideal candidate will be proficient in big data tools like Hadoop, Hive, and Spark, programming languages such as Scala, Python, SQL, and have strong analytical skills related to working with structured and unstructured datasets in Cloud and on-prem environments

This position is based in Visa's offices in Atlanta, USA, and presents an excellent opportunity for those looking to make a significant impact in the field of Data Engineering.

Essential Functions:

  • Experience in Requirement Gathering, Estimating, Managing large scale Data Engineering Projects.
  • Requirement Analysis: Understand and translate business needs into data models supporting long-term solutions.
  • Data Modeling: Work with the Business team to implement data strategies, build data flows and develop conceptual data models.
  • Data Pipeline Design: Create robust and scalable data pipelines and data products in a variety of domains.
  • Data Integration: Develop and maintain data lakes by acquiring data from primary and secondary sources and build scripts that will make our data evaluation process more flexible or scalable across data sets.
  • Testing: Define and manage the data load procedures to reject or discard datasets or data points that do not meet the defined business rules and quality thresholds.
  • Deployment: Implement data strategies and develop physical data models, along with the development teams, data analyst teams and information system team to ensure robust operational data management systems.
  • Understanding of and ability to Implement Data Engineering principles and best practices.
  • Team Leadership: Lead and mentor a team of data engineers. Coordinate with other teams to manage and prioritize projects. Drive strategy, roadmap, and execution of key data engineering initiatives.
  • Stakeholder Management: Collaborate with stakeholders across the organization to understand their data needs and deliver solutions.

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

Qualifications

Basic Qualifications
• 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications
• 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• Extensive experience in big data tools: Hadoop, Hive, and Spark.
• Proficiency in Scala, Python, SQL, and PySpark.
• Experience with Unix/Linux systems with scripting experience in Bash.
• Experience with data pipeline and workflow management tools like Airflow, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with cloud services AWS or Azure.
• Experience with stream-processing systems: Kafka, Spark-Streaming, etc.
• Strong analytic skills related to working with structured & unstructured datasets.
• Proficiency in managing and communicating data warehouse plans to internal clients.
• Experience with building processes supporting data transformation, data structures, metadata, dependency, and workload management.
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.

Other Skills:
• Strong problem-solving skills.
• Excellent communication skills.
• Ability to work in a team.
• Detail-oriented and excellent organizational skills.
• Exposure to Financial Services/ Payments Industry
• Proven leadership skills with experience leading a team of data engineers.
Leadership Competencies
• Exhibits intellectual curiosity and a desire for continuous learning.
• Demonstrates integrity, maturity, and a constructive approach to business challenges.
• Role model for the organization and implementing core Visa Values
• Respect for the Individuals at all levels in the workplace
• Strive for Excellence and extraordinary results.
• Use sound insights and judgments to make informed decisions in line with business strategy and needs.
• Leadership skills include an ability to allocate tasks and resources across multiple lines of businesses and geographies. Leadership extends to ability to influence senior management within and outside Analytics groups.
• Ability to successfully persuade/influence internal stakeholders for building best-in-class solutions.

Additional Information

Work Authorization: Permanent Authorization to work in the U.S. is a precondition of employment for this position. Visa will not sponsor applicants for work visas in connection with this position.

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

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.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $132,000.00 to per $211,300.00 year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

Average salary estimate

$171650 / YEARLY (est.)
min
max
$132000K
$211300K

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 Engineer, Visa

Are you ready to take your career to the next level? Visa is looking for a Staff Data Engineer to join our dynamic team in Atlanta, Georgia. In this role, you’ll have the opportunity to lead and mentor a talented group of data engineers, driving innovative data engineering initiatives that make a real impact within the financial technology landscape. Your expertise will help translate business needs into actionable data models, develop robust data pipelines, and establish data lakes that enhance our decision-making capabilities. You’ll collaborate with a range of stakeholders to ensure that their data needs are met while keeping our data solutions scalable and efficient. With your deep understanding of big data tools like Hadoop and Spark, along with programming prowess in Scala and Python, you’ll be at the core of enabling data-driven strategies at Visa. Not only will you manage existing projects, but you'll also shape the vision and roadmap for future data engineering efforts. Plus, we offer a hybrid working environment, allowing you to balance your professional and personal life effectively. If you’re passionate about leveraging data to drive results and want to be part of a purpose-driven organization that uplifts communities and businesses globally, this is the role for you. Join us at Visa and experience a culture where innovation is embraced, and every team member's contribution matters!

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

As a Staff Data Engineer at Visa, you will lead a team of data engineers, manage large-scale data engineering projects, translate business requirements into effective data models, and design robust data pipelines. You'll also be responsible for developing and maintaining data lakes and implementing operational data management systems to ensure data integrity and accessibility.

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

To apply for the Staff Data Engineer role at Visa, it's preferred that candidates have at least 6 years of relevant experience. Additionally, proficiency in big data technologies such as Hadoop, Hive, and Spark is required, alongside programming skills in Scala, Python, and SQL. A strong analytical skill set for working with both structured and unstructured datasets is crucial.

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How does collaboration play a role in the Staff Data Engineer position at Visa?

Collaboration is vital for a Staff Data Engineer at Visa. You'll be working closely with various stakeholders across the organization to understand their data needs and deliver tailored solutions. This teamwork helps ensure data strategies align with business goals and that the insights generated are impactful.

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What tools and systems does the Staff Data Engineer use at Visa?

The Staff Data Engineer at Visa will work with a range of tools and systems including big data platforms like Hadoop, Hive, and Spark, as well as pipeline management tools like Airflow. Familiarity with both relational SQL and NoSQL databases, cloud services such as AWS or Azure, and stream-processing systems like Kafka is essential for success in this role.

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What growth opportunities are available for a Staff Data Engineer at Visa?

Visa places a strong emphasis on career development and growth. As a Staff Data Engineer, you’ll have opportunities for leadership development, access to continuous learning resources, and the chance to work on high-impact projects that contribute to Visa's strategic objectives, setting you up for future career advancement within the company.

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Common Interview Questions for Staff Data Engineer
Can you describe your experience with big data tools like Hadoop and Spark?

To answer this, share specific projects where you've utilized these tools, detailing the challenges faced and how you effectively leveraged Hadoop or Spark to achieve your objectives. Demonstrating a strong understanding of their functionalities and performance impact will also be beneficial.

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How do you approach data modeling and integrating business needs into technical solutions?

Begin by explaining your process of requirement gathering from stakeholders. Highlight how you translate those needs into structured data models, and mention any frameworks or practices you follow that ensure the solutions are scalable and maintainable.

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Describe your experience leading a team of data engineers. What strategies have you used to ensure project success?

Discuss your leadership style, emphasizing collaboration and mentorship. Provide examples of how you've encouraged knowledge sharing and maintained open communication while successfully managing project timelines and deliverables.

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What are some common data quality issues you’ve encountered and how did you resolve them?

Share specific instances of data quality challenges you've faced, and explain the steps you took to identify and resolve these issues. Mention tools or processes you implemented to ensure data quality moving forward.

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How do you stay updated with the latest trends and technologies in data engineering?

Talk about your commitment to continuous learning, whether through attending industry conferences, pursuing certifications, or being part of professional networks. Mention any specific resources or methods you use to stay informed.

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How have you handled conflicts within your team or project stakeholders?

Provide an example of a conflict you encountered and explain how you facilitated communication to resolve it. Emphasize your focus on finding common ground and ensuring that all voices were heard in the resolution process.

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Can you walk us through a successful data pipeline you’ve built?

This is your chance to showcase your technical expertise. Discuss the goals of the data pipeline, the technologies used, the architecture of the solution, and the outcomes achieved. Be sure to explain any challenges faced and how you overcame them.

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What metrics do you consider for measuring the success of a data engineering project?

Discuss important metrics such as data accuracy, processing time, user satisfaction, and the overall impact on business decision-making. Provide examples of how tracking these metrics helped you enhance project outcomes.

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How do you ensure compliance and data governance in your projects?

Outline your understanding of data governance principles and how you apply them. Discuss specific practices you've put in place to ensure compliance with relevant regulations and internal standards in past projects.

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What experience do you have with cloud services like AWS or Azure?

Talk about the specific cloud services you've used and how you've utilized them in designing scalable data solutions. Mention projects where you leveraged cloud capabilities to enhance efficiency and performance.

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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...

11607 jobs
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Full-time, hybrid
DATE POSTED
March 30, 2025

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