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Staff Data Engineer - job 7 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

Join us as a Staff Data Engineer at Mentor, where you'll be at the heart of our Data Engineering team, forging a connection between technology and product innovation. In this vital role, you'll directly report to the Data Engineering department and play a key role in executing our data strategies and processes in tune with Technology Services standards. Collaborating closely with our Data Solutions Product Manager, you'll dive into exciting projects that influence product development and spark innovation. As the bridge between technical and product realms, your expertise will ensure our data engineering solutions are seamlessly integrated into product initiatives, fostering a culture that values data-driven decision-making. Your responsibilities will include acting as a key player in meetings with stakeholders, identifying critical system and architecture needs, and proficiently analyzing data to support intentional database design. You'll write maintainable, reusable code and conduct independent unit testing to confirm the functionality of your developments. Constructing tools that automate processes and writing queries to gather raw data across pipelines will be everyday tasks. Furthermore, you'll implement self-healing processes to enhance data quality and optimize performance, supporting the growth and success of Mentor. This hybrid position allows for a flexible work environment, ensuring you can collaborate effectively while also enjoying remote work days. Join us in transforming data into valuable insights and be part of our growth story!

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

As a Staff Data Engineer at Mentor, your primary responsibilities include acting as a crucial link between the Data Engineering team and the Product organization. You'll work closely with stakeholders to clarify requirements, identify data needs for applications, analyze data for database design, and implement reliable and reusable code. Additionally, you will conduct thorough unit testing and user acceptance testing while building tools to optimize data processes. Ultimately, your work will drive product innovation and ensure high data quality across the board.

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

To be considered for the Staff Data Engineer role at Mentor, candidates should have a strong background in data engineering, along with a comprehensive understanding of database design and query writing. Proficiency in coding standards, security requirements, and automation processes is crucial. The ideal candidate should also possess excellent communication skills to effectively bridge the gap between technical and non-technical teams, and experience in mentoring others is a significant plus.

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

At Mentor, a Staff Data Engineer plays a pivotal role in shaping product development by integrating data engineering solutions directly into product initiatives. You will work alongside product managers to identify key projects that harness the power of data, foster a data-driven culture, and implement innovative strategies. Your contribution will ensure that the data team’s work aligns closely with product goals, ultimately enhancing the company’s overall success.

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What can I expect from the work culture as a Staff Data Engineer at Mentor?

The work culture at Mentor for a Staff Data Engineer is collaborative, innovative, and supportive. You will engage with cross-functional teams frequently, allowing you to build rich relationships with stakeholders and contribute to decision-making processes. The company promotes a hybrid work environment, allowing you to enjoy the flexibility of remote work while collaborating in-person for essential meetings and teamwork. Overall, you'll be part of a forward-thinking organization that values diversity and creativity in problem-solving.

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What does the hybrid work model look like for a Staff Data Engineer at Mentor?

As a Staff Data Engineer at Mentor, the hybrid work model involves alternating between remote and office work. Employees are expected to be in the office 2-3 set days a week, as determined by leadership and business needs. This flexibility allows you to maintain a work-life balance while still benefiting from in-person collaboration and team bonding, ensuring you remain engaged and connected with your colleagues.

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Common Interview Questions for Staff Data Engineer
Can you explain your experience with data engineering and relevant technologies?

In your response, highlight specific data engineering technologies and languages you have worked with, such as SQL, Python, or Spark. Offer examples of past projects where you've effectively implemented data pipelines or architected databases. Mention any experience you have with tools for data integration and analysis, showcasing your hands-on skills and contributions.

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How do you ensure data quality in your engineering processes?

Discuss the techniques you utilize to maintain data quality, such as implementing data validation checks, conducting regular audits, and setting up monitoring systems. Provide examples of how you've handled data discrepancies or quality issues in past roles, including your approach to identifying the root cause and implementing long-term fixes.

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Describe a challenging project and how you overcame obstacles as a Staff Data Engineer.

Define the project clearly and detail the challenges you faced, whether they were technical hurdles, team dynamics, or timeline pressures. Discuss the strategies you employed to overcome these obstacles, demonstrating your problem-solving skills, adaptability, and collaboration with team members, which can reflect positively on your fit for the role.

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What coding standards do you follow in your development work?

Talk about your familiarity with industry standards, best coding practices, and methodologies such as Agile or DevOps. Explain how you ensure your code is readable, maintainable, and efficient. If applicable, mention any code review practices you've participated in or led, emphasizing teamwork and quality assurance.

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How do you collaborate with product teams to align engineering goals?

Share your approach to communication and collaboration with product managers and cross-functional team members. Highlight specific examples of collaboration tools or strategies you’ve employed to share insights and align goals, such as regular meetings, feedback loops, and joint planning sessions.

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What tools do you use for automating data processes?

List the automation tools and technologies you're familiar with, such as Apache Airflow, Kubernetes, or other ETL tools. Describe how you've applied these tools in past projects to streamline data processes and improve efficiency. Offer examples of automations you've created and how they impacted team productivity.

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Can you discuss a time when you had to mentor someone on your team?

Explain the context of the mentoring situation, the individual’s role, and how you approached providing guidance. Highlight the skills you focused on, the methods you used to facilitate their learning, and any positive outcomes that resulted from this mentorship experience, showcasing your leadership capabilities.

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

Describe the resources you utilize to remain current, such as online courses, webinars, conferences, or professional communities. Share specific examples of how you've applied new knowledge or trends in your work to showcase your commitment to continuous learning and improvement.

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What steps do you take when developing a new data pipeline?

Outline your process step-by-step, starting from designing the pipeline architecture, defining data sources, choosing the appropriate technologies, and coding the pipeline. Discuss how you ensure thorough testing and validation, as well as considerations for scalability and performance in your design.

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How do you handle tight deadlines in data engineering projects?

Share specific strategies you employ to manage your time and prioritize tasks effectively during high-pressure situations. Discuss your experience with Agile methodologies or Kanban boards to illustrate how you keep projects moving forward and ensure timely delivery without sacrificing quality.

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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 4, 2025

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