Staff Data Engineer (6 - 8 years of experience in Golang / Java / Rust, Kafka, ML Ops, Distributed systems)

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

Visa AI as a Service (AIaS) operationalizes the delivery of AI and decision intelligence to ensure their ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud native platforms, AIaS powers and automates industrialization of data, models, and applications. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, Visa AI as a Service is an ideal place for you!

This position is for a Staff Data Engineer with a background in development of distributed backend platforms. The right candidate is one who will focus on creating and maintaining new capabilities for AI as a Service while maturing our platforms and products.

You will be an integral part of the AIaS engineering team, analyzing and implementing new requirements, in a continuous effort to provide better solutions to Visa’s consumers. You must be a self-organized individual should be flexible and willing to switch tasks based on business needs.

If this sounds exciting, we want to chat and tell you more about our work culture and environment and see if this will be a good fit for both of us.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:

• 5 or more years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications:

• 6 or more years of work experience with a Bachelor's Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
• Strong Development experience in more than one of the following: Golang, Java, Python, Rust, and C/C++
• Knowledge of common Big data and Real Time stack such as Hadoop, Spark, Kafka, Redis, Flink and similar technologies
• Hands on experience in building and maintaining data and model engineering pipelines, feature engineering pipelines and comfortable with core ML concepts
• Proven knowledge of successful design, architecture and development using Big Data Hadoop, J2EE and Spark with large data volumes and transaction systems
• Possesses a deep understanding of benefits or drawbacks of different integration patterns
• Experience with GIT, Stash, Maven and Jenkins
• Experience in developing, testing, validating and productizing AL/ML models for high performance use cases will be an added advantage
• Strong interpersonal, facilitation, and effective communication skills both written and verbal and the ability to present complex ideas in a clear, concise way
• Highly driven, resourceful and results oriented
• Demonstrated ability to lead and navigate through ambiguity
• Past experience in Payments knowledge is preferred
• Certification in hybrid cloud computing architecture (Microsoft Azure, AWS, Google Cloud Platform) will be added advantage

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.