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Staff Data Engineer - job 32 of 50

The primary purpose of this role is to serve as a pivotal technical link between the Data Engineering team and the Product organization. Reporting directly to the Data Engineering department, this position will be responsible for executing and aligning data engineering strategies and processes in accordance with Technology Services standards. This person will work closely with the Data Solutions Product Manager to identify and undertake key projects and responsibilities that drive product development and innovation. As a bridge between technical and product realms, this role will ensure seamless integration of data engineering solutions into product initiatives, fostering a data-driven product development culture, and contributing to the overall growth and success of the organization.

 

Essential Functions:

  • Acts as a key player during meetings with stakeholders (e.g., Product teams, business partners, Cybersecurity) to identify and clarify requirements and determine business needs.
  • Identifies systems, architectures, tools, and storage needs that support the requirements for the application for a product.
  • Proficient in analyzing data for the purpose of intentional database design, discovering new potential data use cases and articulating technical requirements.
  • Implements extensible, maintainable and reusable code, using appropriate coding patterns, guidelines, styles and best practices, informally mentoring others, and adheres to all security requirements.
  • Independently conducts unit testing to confirm functional capability of code. Conducts tests for coding standards and security scans. Conducts user acceptance testing in collaboration with customer.
  • Builds tools and standard automation processes that assist in transforming, managing, accessing, deploying, and monitoring data processes in batches and in real time.
  • Independently writes queries to extract and compile raw data across end-to-end pipelines.
  • Implements and monitors self-healing processes across multiple product features to prevent recurring issues, maintain and improve data quality and pipeline, and optimize performance throughout the data lifecycle.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Average salary estimate

$100000 / YEARLY (est.)
min
max
$80000K
$120000K

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

As a Staff Data Engineer at Mentor, you'll play a crucial role in linking the Data Engineering team with the Product organization. This position is all about fostering collaboration and innovation as you execute data engineering strategies and adhere to technology standards. Working closely with the Data Solutions Product Manager, you'll take on key projects that drive product development and contribute to a data-driven culture. You'll find yourself at the center of meetings with stakeholders, where you'll clarify requirements and ensure alignment between technical and business needs. Your technical expertise will be called upon as you analyze data, identify system needs, and implement maintainable code following best practices. Enjoy the creativity of building tools and automation processes that manage and transform data efficiently. You’ll be responsible for ensuring the integrity of data pipelines through unit testing and user acceptance testing. Plus, as a hybrid role, you'll enjoy the flexibility of working remotely while maintaining a presence in the office 2-3 days a week. If you're passionate about leveraging data to fuel product innovation, the Staff Data Engineer position at Mentor could be the perfect fit for you!

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

The Staff Data Engineer at Mentor plays a vital role by acting as a bridge between the Data Engineering team and Product organization. Key responsibilities include collaborating with stakeholders to understand requirements, identifying systems and tools for product support, crafting maintainable code, and performing rigorous testing to ensure data quality. Additionally, this position involves building automation processes and monitoring data products to enhance performance, ultimately contributing to a robust data-driven culture.

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What qualifications are required for the Staff Data Engineer role at Mentor?

To thrive as a Staff Data Engineer at Mentor, candidates should have a strong background in data engineering, proficient coding skills, and experience with database design and data pipelines. It's advantageous to have familiarity with coding best practices and data management tools. A relevant degree in Computer Science or a related field, coupled with practical experience in data-driven environments, makes for an ideal candidate.

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How does the Staff Data Engineer role at Mentor contribute to product development?

In the Staff Data Engineer position at Mentor, you'll directly influence product development by ensuring that data engineering practices align with product goals. By analyzing data requirements, creating effective solutions, and fostering collaboration across teams, you’ll enable better decision-making and innovation within product initiatives. Your expertise will ensure that data is leveraged effectively, enhancing the overall product quality and success.

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What is the work environment like for a Staff Data Engineer at Mentor?

The work environment for a Staff Data Engineer at Mentor is a hybrid setup, allowing for a mix of both remote work and in-office collaboration. Expect to work in a dynamic team where communication and innovation are key. You’ll spend 2-3 days in the office, with the remainder of your time spent remote, striking a balance that encourages productivity and work-life integration.

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What types of projects can a Staff Data Engineer at Mentor expect to work on?

A Staff Data Engineer at Mentor can expect to tackle a variety of exciting projects, including developing new data pipelines, optimizing existing processes, and implementing data management solutions that drive product innovation. You will work closely with both technical teams and product managers to ensure that data engineering solutions are seamlessly integrated into ongoing product initiatives, fostering a culture that prioritizes data-driven decision-making.

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Common Interview Questions for Staff Data Engineer
Can you describe a challenging data engineering project you managed?

When answering this question, focus on the specific project challenges, your role in managing those obstacles, and the outcomes achieved. Highlight your problem-solving skills, collaboration with stakeholders, and any innovative solutions or technologies you implemented.

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How do you ensure the quality of data in your engineering processes?

Discuss the testing procedures you follow, such as unit testing, user acceptance testing, and monitoring for data integrity. Emphasize the importance of establishing quality assurance workflows and your experience with tools or methodologies that support data quality.

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What coding practices do you follow to maintain code quality?

Talk about your commitment to coding standards and best practices, including documentation, code reviews, and style guidelines. Additionally, mention any languages or frameworks you are particularly skilled in, and how those contribute to maintainable and scalable code.

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How do you approach collaboration with non-technical teams?

Explain your communication strategies when working with product managers and other non-technical stakeholders. Emphasize your ability to translate complex technical concepts into easily understandable terms, which fosters collaboration and efficient project outcomes.

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What experience do you have with data automation and management tools?

Outline your experience with specific tools and technologies used for data automation, such as ETL (Extract, Transform, Load) processes or any relevant platforms. Discuss how you have implemented automation solutions that improved operational efficiency.

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How do you keep up with trends and advancements in data engineering?

Talk about your commitment to continual learning, whether through online courses, attending conferences, or participating in professional communities. Mention specific areas of interest or recent trends that excite you and how they might be relevant to the Staff Data Engineer role.

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Can you explain your experience with data pipeline architecture?

Describe your familiarity and practical experience with building and managing data pipelines, including any frameworks or tools you've utilized. Illustrate the importance of pipeline architecture in ensuring efficient data flow and accessibility across various applications.

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How do you handle pressure when working on tight deadlines?

Share your strategies for managing stress and maintaining productivity under pressure. Discuss your time management skills, prioritization techniques, and any tools you use to stay organized when faced with challenging deadlines.

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What is your approach to troubleshooting data issues?

Explain your methodology for diagnosing and resolving data issues, which may include systematic testing, collaboration with team members, and leveraging analytical tools to trace problems back to their source. Emphasize your analytical skills and experience in problem-solving.

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Why do you think data is important for product development?

Illustrate your understanding of the significance of data in driving product decisions and innovations. Discuss how leveraging data can enhance user experience, inform feature development, and shape overall product strategy.

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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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April 3, 2025

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