Staff Data Engineer
Staff Data Engineer
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Job Description
The role offers a unique blend of Data Engineering and Machine Learning Engineering tasks emphasizing strong software development practices. The successful candidate will collaborate with a team to conduct world-class applied data and AI project on financial payments driving innovation in alignment with Visas strategic vision by incubating new data- and AI-powered products and enhancing existing applications with data engineering machine learning and AI. This role represents an exciting opportunity to make key contributions to Visas strategic vision as a world-leading data-driven company. The successful candidate must have strong data software engineering distributed computing and machine learning skills. You will be a self-starter comfortable with ambiguity with strong attention to detail and excellent collaboration skills.
We are looking for a skilled Engineer with expertise in both Data Engineering and Machine Learning to take ownership of our data and machine learning solutions. You will be responsible for establishing best practices in our processes - which include data management preprocessing code management tool selection distributed computing and cloud infrastructure. Your work will be foundational to enabling our data science and ML teams to deliver at scale reliably and with high standards.
You will engage with different collaborators senior executives research scientists software engineers and architects as well as external parties like technology vendors wallet providers merchants issuers and senior product regional managers. You will discover and propose research and development opportunities build development plan create and implement the ideas.
You will have the opportunity and the responsibility to build the long-term vision for the payment industry and influence the direction of the innovation and development across Visa.
Essential Functions
Lead the design implementation and maintenance of robust data & ML pipelines for ingesting and processing the data and training and deploying ML models.
Establish standards and best practices for data code and pipeline management versioning and governance for ensuring reusability scalability and 1
Evaluate recommend and implement tooling for data science and ML workflows including experiment tracking model management and reproducibility.
Own the setup of distributed computing resources (on-premises or cloud such as AWS) ensuring scalability and cost efficiency.
Collaborate with Data Scientists ML Engineers and other stakeholders to understand requirements and enable efficient model development deployment and monitoring.
Drive automation of ML pipelines (MLOps): from data ingestion and preprocessing to model training validation deployment and monitoring.
Mentor and guide junior engineers and data scientists in engineering best practices code reviews and project planning.
Document processes decisions and systems to ensure maintainability and knowledge sharing within the team.
Stay current with industry trends and emerging technologies in data engineering distributed computing and MLOps.
Collaborate with research scientists product owners and architects to deliver the fast-prototyping platform.
Champion the innovation across the organizations and industries as an expert in the subject either by providing consulting or by contributing to technology talks and presentations.
Make decision on trade-offs/priority during the design and execution such as trade-off between performance and flexibility scope and timelines availability and scalability etc.
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 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
Preferred Qualifications
Bachelors Masters or PhD degree in Computer Science Engineering Mathematics or a related field (or equivalent experience).
7 years of directly related experience in data engineering machine learning engineering or related fields.
Strong software engineering skills including experience with modular code design automated testing code reviews and documentation to ensure maintainable and scalable solutions.
Expertise with cloud platforms (preferably AWS) especially cloud-native data and ML services.
Strong understanding of algorithms and data structures.
Proven experience architecting and managing data pipelines (ETL/ELT) especially for ML/AI applications.
Proven experience developing and maintaining machine learning lifecycle: data preprocessing and feature extraction model training and evaluation and deployment and monitoring.
Excellent programming skills in Python (and optionally Scala Java). Strong with data processing frameworks (e.g. Spark Dask Pandas Airflow).
Experience with distributed computing and handling of large-scale data.
Hands-on experience with ML workflow tools (MLflow Kubeflow SageMaker Vertex AI etc.) and model deployment (REST APIs containers CI/CD).
Deep knowledge of version control (git) and best practices for codebase organization in multi-person teams.
Familiarity with data governance security and compliance standards (GDPR HIPAA etc. as relevant).
Excellent communication and documentation skills.
Demonstrated ability to take ownership and drive projects from inception to completion in a fast-paced ambiguous environment.
Familiarity with data visualization and BI tools.
Contributions to open-source projects in data engineering or ML is a plus
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.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
