Data Engineer-, Big Data, Java- 6 months - 1.6 yrs exp

As a Data Engineer at Visa, your primary responsibilities include translating business requirements into technical solutions using Big Data and Java, collaborating with business partners for clarity on requirements, designing and developing software components, and documenting processes for maintenance. You will also be involved in writing unit tests and integrating test frameworks, taking ownership of code production deployment, and ensuring adherence to coding and design best practices.

To apply for the Data Engineer position at Visa, you should have a Bachelor's degree in Computer Science, Electrical Engineering, Information Systems, or a related technical field. The role requires at least one year of software development experience, particularly in Hadoop using Spark and Scala. Proficiency in programming languages like Java and Python, and familiarity with CI/CD processes and version control tools are also essential.

For the Data Engineer position at Visa, strong programming skills in Object-Oriented Programming languages such as Java and Python are crucial. Additionally, experience in using Hadoop along with tools like Spark and Scala will significantly benefit your application, as well as knowledge of CI/CD processes and automation methodologies relevant to data operations.

The work environment for a Data Engineer at Visa is primarily hybrid, meaning you can expect a mix of remote and in-office work. This flexibility allows you to thrive in a self-motivated space while collaborating with your team to meet the fast-paced demands of the payments industry. Visa promotes an internal innovation-driven atmosphere that encourages employees to embrace new technologies and adapt the solutions accordingly.

Visa is committed to professional development for its Data Engineers through ongoing training, mentoring programs, and opportunities to work on cutting-edge projects that enhance your skills. The culture emphasizes collaboration and sharing knowledge within teams, thereby fostering an environment where you can continuously learn and grow in your career.

When answering this question, focus on the specific challenges you faced, the technologies you used, and how you overcame those obstacles to achieve a successful outcome. Highlight your problem-solving skills and the impact your contributions had on the project.

Discuss the importance of writing unit tests, following best coding practices, and conducting peer reviews. Highlight your experience with data validation and error handling to ensure the reliability of your solutions.

Clearly outline your practical experience with both Hadoop and Spark, describing any specific projects where you implemented these technologies. Mention any challenges you faced and the results achieved through your use of these tools.

Explain your proficiency with version control systems like Git. Discuss how you manage branches, merges, and resolve conflicts, emphasizing the importance of maintaining well-documented code versions for collaboration.

Share your systematic approach to identifying and resolving data issues. Describe the tools you use for monitoring and diagnosing problems, as well as any techniques you apply to trace issues effectively.

Mention specific resources like blogs, webinars, and online courses you utilize to stay informed. Discuss any communities you engage with or conferences you attend to network and learn about emerging technologies.

Provide details about your familiarity with CI/CD tools and pipelines. Discuss how these practices have improved your deployment processes and the impact they have on your development cycles.

Explain your approach to time management and task prioritization, possibly using tools or methodologies (like Agile) that help you focus on deliverables and maintain quality across projects.

Identify essential qualities such as analytical thinking, attention to detail, teamwork, and adaptability. Provide examples of how you've exemplified these traits in your work.

Discuss your communication strategies, whether it's through regular check-ins, shared documentation, collaboration tools, or agile scrums. Emphasize the importance of keeping everyone aligned and informed throughout project lifecycles.