Staff Data Engineer

Visa•Austin, TX

18h•$133,300 - $213,400•Hybrid

About The Position

As a Staff Data Engineer, you'll join our Value Added Services – Digital Marketing & Engagement organization. You will help design, enhance, and build our Visa data token platform within an agile development environment, collaborating with colleagues who will support and challenge you daily.

Requirements

5 or more years of relevant work experience with a Bachelors 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.
Demonstrated leadership in delivering high-quality, large-scale, enterprise-class applications.
Solid experience in big data engineering, with knowledge of Hadoop, Apache Spark, Python, and SQL.
Experience in Docker, Kubernetes for containerization
Proficiency in creating and managing large-scale data pipelines and machine learning models.
Experience developing ETL processes, maintaining Spark pipelines, and productizing AI/ML models.
Proficient in technologies like Kafka, Redis, Flink, TensorFlow, Triton, and AWS services.
Skilled in Unix/Shell or Python scripting and scheduling tools like Airflow and Control-M.
Familiarity with Agile development, TDD, CI/CD, and various databases.
Proven track record of building reliable, scalable, and operable applications.
Ability to manage component security analysis and collaborate with security teams.
Strong work ethic, focus on immediate goals, and proven experience as a technical leader.
Passion for mentoring and helping juniors grow professionally.
Excellent communication and interpersonal skills, and a strong team player.

Nice To Haves

6 or more years of work experience with a Bachelors 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

Responsibilities

Design, build, and optimize large-scale data pipelines for batch and real-time processing
Develop and maintain distributed data systems that are highly available, scalable, and resilient
Lead initiatives to process, transform, and manage structured and unstructured data across platforms
Drive development of data platforms and data products that support analytics, reporting, and machine learning use cases
Partner with product, analytics, and business teams to translate requirements into scalable data solutions
Architect solutions using big data technologies such as Hadoop, Spark, and distributed data processing framework
Build and optimize ETL/ELT pipelines and ensure high data quality, reliability, and performance
Implement automation, monitoring, and observability for data pipelines across the data lifecycle
Lead proof-of-concept initiatives to evaluate and adopt new data engineering technologies
Influence and drive best practices in data engineering, including data modeling, pipeline design, and governance
Mentor engineers and foster a culture of continuous learning and accountability.
Collaborate with stakeholders to understand data requirements and deliver impactful solutions
Architect and implement secure, robust, and scalable data platforms
Drive innovation through experimentation, prototyping, and rapid iteration
Ensure strong data governance, quality, and operational excellence
Engage with cross-functional teams to align on technical and business outcomes