Data Engineer - Sr. Consultant level - job 15 of 19

As a Data Engineer - Sr. Consultant at Visa Technology & Operations LLC, your primary responsibilities include designing and enhancing fraud detection solutions, collaborating with cross-functional teams to develop data-driven solutions, mentoring junior engineers, and ensuring project delivery within established timelines and budgets. You will be involved in all phases of solution development, focusing on performance metrics and data governance.

The Data Engineer - Sr. Consultant role at Visa Technology & Operations LLC typically requires a strong background in data engineering, a degree in computer science or a related field, and several years of experience in a relevant domain. Proficiency in programming languages, data modeling, and experience with big data technologies are highly desirable. Additionally, strong analytical, problem-solving, and communication skills are essential.

In the Data Engineer - Sr. Consultant role at Visa Technology & Operations LLC, you will contribute to fraud detection by designing and implementing sophisticated data solutions that identify fraudulent activities. This involves engaging in collaborative efforts with stakeholders to ensure that business problems are accurately translated into data challenges, ultimately leading to effective fraud detection mechanisms.

Yes, the Data Engineer - Sr. Consultant position at Visa Technology & Operations LLC allows for partial telecommuting. This flexibility enables you to work effectively while balancing your professional and personal commitments, contributing to a healthy work-life balance.

The work environment for a Data Engineer - Sr. Consultant at Visa Technology & Operations LLC is collaborative and innovative. You will have the opportunity to work with talented professionals from various disciplines in an agile development setting. The culture emphasizes continuous learning, mentorship, and the pursuit of excellence in data engineering solutions.

In my previous roles as a Data Engineer, I have been instrumental in developing data models that optimized data storage and retrieval. My experience includes working on both relational and NoSQL databases, ensuring that architecture decisions align with both current and future business needs. I emphasize documenting every architectural decision to provide clarity for team members.

To handle tight deadlines, I prioritize tasks based on urgency and business impact, ensuring that critical projects receive the attention they require. I make use of project management tools to keep track of progress and communicate transparently with my team. Adapting quickly to change is vital, and I ensure to remain agile in my approach.

I employ multiple strategies to ensure data quality, including implementing automated data validation checks, conducting root cause analysis for data discrepancies, and maintaining accurate documentation of data sources and transformations. Regular collaboration with stakeholders to understand their data needs is also key to ensuring quality.

In one challenging project, I was tasked with integrating disparate data sources to create a unified reporting system. The key challenge was managing varying data quality and format inconsistencies. By implementing a tiered data cleaning approach and working closely with stakeholders for requirements gathering, we not only delivered on time but also improved reporting accuracy significantly.

I believe in fostering an open and inclusive learning environment, so I approach mentoring by pairing junior engineers with experienced team members for real-time guidance. I also conduct regular knowledge-sharing sessions and encourage them to ask questions. My goal is to empower them to take ownership of their learning journey.

I frequently use tools such as Apache Spark for big data processing, SQL for querying databases, and Git for version control. These tools enhance my productivity and collaboration, allowing me to efficiently manage data pipelines and track changes across projects over time.

I have implemented several data governance practices, such as developing data classification schemas, establishing data stewardship roles, and enforcing access controls to sensitive data. These practices ensure compliance with regulations and maintain organizational data integrity.

To stay updated with the latest trends in data engineering, I regularly follow industry publications, engage with online communities, and participate in data meetups and webinars. Continuous learning is vital, and I always look for opportunities to enhance my skill set.

My experience in an agile development environment has been focused on adaptability, collaboration, and iterative progress. I actively participate in SCRUM meetings, sprint planning, and retrospectives to ensure that our team remains aligned on objectives and can promptly tackle any obstacles that arise.

I believe that problem-solving skills are the most critical for a Data Engineer. The ability to analyze complex business challenges and track down effective technical solutions is invaluable. Coupled with technical proficiency and the capacity for effective communication, this skill ensures success in the role.