Sr. Data Engineer, AWS

Company Description

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

Team Summary

The Risk and Identity Solutions (RaIS) team provides risk management services for banks, merchants, and other payment networks. Machine learning and AI models are the heart of the real-time insights used by our clients to manage risk. Created by the Visa Predictive Models (VPM) team, continual improvement and efficient deployment of these models is essential for our future success. To support our rapidly growing suite of predictive models we are looking for engineers who are passionate about managing large volumes of data, creating efficient, automated processes and standardizing ML/AI tools.

This is a great opportunity to work with a new Engineering and MLOps team to scale and structure large scale data engineering and ML/AI that drives significant revenue for Visa. As a member of the Risk and Identify Solutions modeling organization (VPM), your role will involve developing and implementing practices that will allow deployment of machine learning models in large data science projects.

You must be a hands-on expert able to navigate both data engineering and data science disciplines to build effective engineering solutions that support ML/AI models. You will partner closely with global stakeholders in RaIS Product, VPM Data Science and Visa Research to help create and prioritize our strategic roadmap. You will then leverage your expert technical knowledge of data engineering, tools and data architecture in the design and creation of the solutions on our roadmap.

Essential functions

Team members working for this role deploy, manage, and optimize data pipelines and machine learning models in production environments, ensuring smooth integration and efficient operations. The team also takes a data scientist’s model and make it accessible to the software that utilizes it. The essential functions of this role include:

• ETL processes: The role also involves developing and executing large scale ETL processes to support data quality, reporting, data marts, and predictive modeling.
• Spark pipelines: The role requires building and maintaining efficient and robust Spark pipelines to create and access data
• AWS Services: Knowledge of various AWS services like Redshift, RDS, DynamoDB, EMR, S3, Glue, Kinesis, and Data Pipeline is crucial.
• Programming Languages: Proficiency in languages such as Python, Java, or Scala.
• ETL Tools: Familiarity with ETL (Extract, Transform, Load) tools and processes.
• SQL and NoSQL Databases: Comfortable working with both SQL and NoSQL databases.
• Data Modeling: Understanding of data modeling and structures, metadata, schema, and distributed storage.
• Data Management: Ability to preprocess and clean data, analyze and visualize it, which often requires knowledge of SQL and tools like Hadoop or Spark.
• Big Data Tools: Familiarity with big data platforms like Hadoop, Spark, and Hive.
• DevOps Tools: Knowledge of CI/CD pipeline, version control systems like Git, and container tools like Docker.
• Problem-Solving Skills: Strong analytical and problem-solving skills are essential.
• Collaboration with Technology teams: The role involves working with Data Science teams, Visa Research, and other Technology teams to leverage and provide feedback on ML systems and tools.
• Communication Skills: Ability to communicate complex data insights in a clear and understandable manner to stakeholders.
• Technical documentation and innovation: The role requires defining and building technical and data documentation, using code version control systems, ensuring data accuracy and consistency, and suggesting new ideas for innovation.

Skills which are plus to have:

Understanding of AWS services: Familiarity with AWS services such as S3, EC2, Lambda, and more importantly, AWS machine learning services like SageMaker, Rekognition, etc. Machine Learning Algorithms: Proficiency in a variety of machine learning algorithms and models like linear/logistic regression, random forest, boosting, neural networks etc. Deep Learning Frameworks: Familiarity with deep learning frameworks such as TensorFlow, PyTorch, Keras, etc. DevOps Tools: Understanding of MLOps tools and practices, CI/CD pipeline, version control systems (like Git), and containerization tools (like Docker).

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Bachelors degree in technology with 3 plus years of experience or Masters in technology with 2 plus years of experience or having PHD in technology area or relevant area of expertise for plus years.

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.