Visa-posted 7 days ago
Full-time • Mid Level
Hybrid • Austin, TX
5,001-10,000 employees

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid. Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa. Job Description Visa U.S.A. Inc., a Visa Inc. company, needs a Sr. Data Engineer (multiple openings) in Austin, Texas to: Design, build, and launch efficient and reliable data pipelines to move data (both large and small amounts) in/out of Hadoop Data lake. Architect, build, and launch new data pipelines and models that provide intuitive analytics to customers. Design and develop new systems and tools to enable customers with data analysis and enhanced understanding of their data. Create, automate, and scale repeatable analysis and build self service tools for business users. Execute data engineering projects ranging from small to large individually and as part of project team. Work across multiple teams in high visibility roles and own the solution end-to-end. Assist in scoping and designing analytic data assets. Build and maintain robust data engineering process to develop and implement self-serve data. Perform other tasks on R&D, data governance, system infrastructure, and other cross team functions. Position reports to the Austin, Texas office and may allow for partial telecommuting.

  • Design, build, and launch efficient and reliable data pipelines to move data (both large and small amounts) in/out of Hadoop Data lake.
  • Architect, build, and launch new data pipelines and models that provide intuitive analytics to customers.
  • Design and develop new systems and tools to enable customers with data analysis and enhanced understanding of their data.
  • Create, automate, and scale repeatable analysis and build self service tools for business users.
  • Execute data engineering projects ranging from small to large individually and as part of project team.
  • Work across multiple teams in high visibility roles and own the solution end-to-end.
  • Assist in scoping and designing analytic data assets.
  • Build and maintain robust data engineering process to develop and implement self-serve data.
  • Perform other tasks on R&D, data governance, system infrastructure, and other cross team functions.
  • Employer will accept a Master’s degree in Computer Science, Management Information Systems, or Business Analytics and 2 years of experience in Information Technology or Data Engineer-related occupation.
  • Proficient in utilizing Hadoop for distributed storage and large-scale data processing, enabling efficient handling of massive datasets.
  • Proficient in leveraging Apache Spark for large-scale data processing and advanced analytics, enabling both near real-time data insights and efficient batch processing.
  • Proficient in coding with PySpark, Scala, and Python for scalable data processing, transformation, and analysis, enabling seamless integration with big data frameworks.
  • Knowledge in designing, implementing, and managing both relational (RDBMS) and non-relational (NoSQL) database management systems to ensure efficient data storage, retrieval, and scalability.
  • Proficient in crafting and optimizing complex SQL queries for efficient data retrieval and manipulation, ensuring high performance and reducing query execution times.
  • Proficient in advanced database performance tuning, including indexing strategies and query optimization, to significantly enhance overall system efficiency and responsiveness.
  • Skilled in Presto, Impala, SparkSQL, and Hive for performing SQL-like querying on big data, facilitating extensive data analysis and reporting.
  • Skilled in data modeling and data warehousing techniques to design and implement efficient, scalable, and robust data storage solutions that support business intelligence initiatives.
  • Proficient in utilizing data visualization and business intelligence tools such as Tableau and Power BI to create insightful, interactive reports and dashboards that drive data-driven decision-making.
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