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Staff Data Engineer - job 16 of 50

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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.

What You Should Know About Staff Data Engineer, Visa

Join our innovative team at Mentor as a Staff Data Engineer, where you will play a crucial role in bridging the gap between our Data Engineering team and the Product organization. This exciting position involves working closely with our Data Solutions Product Manager, identifying essential projects that drive product development and innovation. As a Staff Data Engineer, you'll be responsible for implementing data engineering strategies that align with our Technology Services standards, ensuring the seamless integration of our solutions into product initiatives. You’ll foster a data-driven culture within the product team, helping to shape the development process and contribute to the organization’s overall success. Your role will include clarifying project requirements with stakeholders, analyzing data to facilitate intentional database design, and maintaining top-notch coding practices. You’ll also mentor your peers, develop tools for data management, and optimize data processes to enhance performance. This hybrid position allows for flexibility, with the expectation to collaborate in the office 2-3 days a week. If you're passionate about innovating through data and ready to make an impact, we invite you to apply and become part of our growth at Mentor.

Frequently Asked Questions (FAQs) for Staff Data Engineer Role at Visa

What are the primary responsibilities of a Staff Data Engineer at Mentor?

The Staff Data Engineer at Mentor primarily serves as the technical link between the Data Engineering team and Product organization. Responsibilities include identifying requirements through collaboration with stakeholders, analyzing data for database design, writing efficient queries for data extraction, and developing tools and automation processes to manage data operations effectively.