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
Primary Responsibilities
Design: Lead the data pipeline designs as per the defined architecture of the metric repository, using/building re-usable functions and frameworks ensuring scalability, reliability and performance.
Data Analysis: Understand the metric definitions, perform the analysis and lead the discussions with the requestors from across the regions to define the calculation logic and mapping from the source data assets
Data Pipeline Development: Lead a team of data engineers to develop end to end data pipelines to create the new metrics of the metric repository and re-engineer scripts created by the data science teams, such that they can be easily plugged into existing ML Ops frameworks.
AI/ML: Design and develop the integration of the AI/ML model outputs into the metric repository, build the ML Ops components to support and manage the lifecycle of AI based models built by the regional and global data science teams.
Data Quality and Governance: Ensure and enforce the defined data quality standards around data accuracy, integrity and consistency across all deliverables and client deliveries.
Code Review and Best Practices: Conduct code reviews and ensure adherence to best practices in development and deployment. Define and build technical documentation and adherence to the CI/CD processes.
Operations: Support the generation and delivery of Insight feeds to clients, on-time and with the required data quality checks.
Team Management & Collaboration: Collaborate with Data engineers, Data scientists and various groups within the organization to identify areas of improvement, bottlenecks and re-use existing frameworks/processes.
Technical skills
Experience in building large globally applicable data platforms using different data modelling, data storage and data flow techniques to support the technical and business use cases and a solid understanding of best practices in data engineering
Experience with machine learning model inference, validation, deployment and management of BAU operations.
Strong programming skills in building data pipelines using PySpark, Hive, Airflow.
Experience working with scheduling tools (Airflow, Oozie) or building data processing orchestration workflows.
Hands-on experience working with large scale data ingestion, processing, and storage in the Hadoop ecosystem
Experience in writing and optimizing SQL queries in Big data environment.
Experience in creating data dictionaries, setup and monitor data validation alerts, and execute periodic jobs to maintain data pipelines for completed projects
Experience working in Linux/Unix environment and exposure to command line utilities.
Experience creating/supporting production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems.
Experience working in building and integrating the code in the defined CI/CD framework using git.
Experience in drafting solution architecture frameworks that rely on API’s and micro-services
Strategic and Functional Excellence
Good business acumen to orient data analysis to business needs of clients, including experience in the payments space.
Ability to translate data and technical concepts into requirements documents, business cases and user stories.
Good understanding of agile working practices and related program management skills.
Should have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.
Excellent communication and presentation skills with ability to interact with different cross-functional team members at varying levels
Ability to learn new tools and paradigms as data science continues to evolve at Visa and elsewhere.
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
Basic Qualifications
-8+ years of relevant work experience with a Bachelor’s Degree or 7+ years of
relevant work experience with a Master's or Advanced Degree with specialization
in Computer science, Information science, Data Engineering and Analytics or
relevant area.
Preferred Qualifications
-5+ years of experience around development of centralized data repositories
Familiarity with shared services, consulting, financial services is a strong 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.
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