Lead Data Engineer- Data Serving - job 2 of 21

As a Lead Data Engineer at Visa, your responsibilities include providing hands-on technical leadership to ensure your team delivers high-quality, scalable solutions. You'll lead the design and development of secure systems while enforcing best practices for software development and engineering excellence. Additionally, you will work with distributed teams on technical challenges and facilitate knowledge transfer to ensure smooth deployment and operation.

To be a successful Lead Data Engineer at Visa, candidates should possess strong experience in data engineering and technical leadership. A suitable degree in Computer Science, Engineering, or a related field is typically required. A proven track record of delivering scalable solutions and mentoring teams is essential, along with coding proficiency in multiple programming languages.

The hybrid work model for the Lead Data Engineer at Visa allows employees to alternate between remote and office work, providing flexibility. Team members are expected to work from the office three days a week, which fosters collaboration while also giving the freedom to work remotely at other times. This balance promotes both team engagement and individual productivity.

The Lead Data Engineer at Visa will lead a diverse and passionate team of data engineers based in Foster City. You will mentor and guide them through complex project requirements, fostering a culture of innovation and collaborative problem-solving. Your leadership will empower team members to make technical decisions that align with business goals while cultivating a high-performing engineering environment.

The Lead Data Engineer plays a critical role in minimizing Risk and Fraud within the Visa ecosystem by building comprehensive data-driven solutions that help understand consumer behavior. Through the development of innovative platforms and solutions, the engineer will provide insights that support data-backed decision-making, ultimately strengthening Visa's commitment to secure payment solutions.

In my previous roles, I have successfully managed a data engineering team by setting clear goals, promoting collaboration, and providing regular feedback. I prioritize creating an environment that empowers team members, encouraging them to present their ideas and take ownership of their projects.

I typically prefer utilizing cloud-based solutions such as AWS or Google Cloud for their scalability and reliability. For data processing, technologies like Apache Spark or Hadoop are my go-to options, while databases like PostgreSQL or MongoDB are great for handling structured and unstructured data.

Ensuring quality and efficiency in projects involves implementing best practices such as code reviews, automated testing, and continuous integration. Additionally, I focus on fostering a culture of knowledge-sharing and learning within the team to keep everyone updated on the latest methodologies and tools.

One challenging project involved integrating disparate data systems to create a unified data repository. This required navigating complex requirements and aligning various stakeholders, but through clear communication and by leveraging Agile methodologies, we delivered a scalable solution that exceeded expectations.

Tackling risk assessments begins with identifying potential vulnerabilities and threats in data handling processes. Conducting both qualitative and quantitative assessments helps centralize risks, and I work with my team to design solutions that incorporate robust security measures, including encryption and access controls.

I believe in a hands-on approach to mentoring where I actively engage with team members through pair programming and one-on-one sessions. My focus is on setting individual growth plans that align with their career aspirations while providing constructive feedback to guide their development.

I stay updated with the latest trends in data engineering by regularly attending industry conferences, participating in online courses, and subscribing to technology blogs and forums. Engaging with the data engineering community also allows me to share insights and learn from peers in the field.

I excel in languages such as Python, Java, and Scala, which are pivotal in data engineering tasks. Additionally, I am proficient in using tools like Apache Airflow and dbt for workflow orchestration and data transformation, ensuring data integrity and reliability.

In a fast-paced environment, I prioritize tasks by assessing their impact on the project’s goals and deadlines. Utilizing Agile principles, I break down larger tasks into manageable parts and regularly communicate with my team to adjust priorities based on project needs.

Collaboration is crucial in my role as a Lead Data Engineer. Working with cross-functional teams not only fosters innovation but also ensures that all perspectives are considered in the solution development process. I promote regular meetings to facilitate open communication and align our strategic goals.