Associate Data Engineer

As an Associate Data Engineer at Visa, you will manage system requirements and lead the design and development of data solutions. Your responsibilities include collaborating with product owners and stakeholders to identify business needs, scoping and designing analytic data assets, and building self-service tools. You'll also work on executing data engineering projects, ensuring high-quality deliverables, and continuously optimizing existing solutions.

To qualify as an Associate Data Engineer at Visa, you need at least a bachelor's degree or 3 years of relevant experience. Preferred qualifications include experience building data engineering pipelines, familiarity with Big Data technologies like Hadoop and Spark, and proficiency in programming languages like Python or Java. Understanding cloud platforms and ETL tools is also advantageous.

Visa places a strong emphasis on employee growth and development. As an Associate Data Engineer, you will have access to resources and opportunities for continuous learning in the data engineering domain. You'll work alongside experienced professionals who can mentor you, and you'll participate in brainstorming sessions to foster creativity and innovation.

Success as an Associate Data Engineer at Visa requires strong problem-solving abilities, proficiency in data engineering tools and programming languages, and expertise in cloud technologies. Additionally, a solid understanding of database management, ETL processes, and Agile methodologies will be crucial in delivering high-quality data solutions.

The working environment for an Associate Data Engineer at Visa is collaborative and innovative. You'll work in a hybrid model where you can enjoy the flexibility of remote work while also engaging with your team in the office. Visa fosters a culture that values quality, accountability, and continuous improvement, providing you a supportive backdrop to make impactful contributions.

When designing data pipelines as an Associate Data Engineer, I follow a structured approach which starts with understanding the requirements from stakeholders. I prioritize scalability, reliability, and performance, choosing the right tools and technologies. Additionally, I ensure I document every step to maintain transparency and facilitate communication with team members.

Cloud technologies in data engineering are crucial as they provide scalability, flexibility, and cost-effectiveness. They offer vast computing resources and services that can handle varying workloads, which is vital for processing large data sets efficiently. Understanding the cloud landscape helps in selecting the right services for data storage, processing, and analytics.

I have hands-on experience with several ETL tools, including Informatica and Azure Data Factory. In previous projects, I have utilized these tools to extract data from multiple sources, transform it according to business needs, and load it into the target databases while ensuring data integrity and quality.

In a previous role, I worked on a project that involved migrating a complex data environment to a cloud solution. The challenge was ensuring minimal downtime and data loss during the transition. By meticulously planning and conducting tests, I successfully executed the migration while optimizing the data flow, leading to improved performance.

I ensure data quality by implementing strict validation checks throughout the data pipeline. This includes automated testing and continuous monitoring to catch discrepancies early. Additionally, I maintain documentation and collaborate with data owners to establish standards for data accuracy and reliability.

I am most proficient in Python and Scala, which I utilize frequently in data processing and pipeline development. My understanding of object-oriented programming principles enables me to write efficient and maintainable code, which is essential in a data engineering environment.

I prioritize my tasks based on project deadlines and their complexity. I use project management tools to keep track of my progress and ensure I meet milestones. By breaking down projects into manageable sections, I can focus my efforts on delivering quality results on time.

I have significant experience with data warehousing, including designing and implementing data models that facilitate reporting and analysis. I have worked with relational databases like SQL Server and Oracle to create efficient data structures that ensure quick data retrieval for end-users.

I am quite familiar with Agile methodologies, having participated in Agile/Scrum teams where I contributed to sprints, conducted stand-ups, and collaborated closely with cross-functional teams. This experience has enhanced my ability to adapt to changing requirements and deliver value quickly.

I am drawn to Visa because of its commitment to innovation and excellence in the payments industry. I believe my skills in data engineering can contribute to Visa's mission, and I'm excited about the potential for professional growth within an organization that values creativity and collaboration.