Data Science Consultant

Job Summary

The Client Services BI & Analytics team strives to create an open, trusting data culture where the cost of curiosity – the number of steps, amount of time, and complexity of effort needed to use operational data to derive insights – is as low as possible. We govern Client Services’ operational data and metrics, create easily usable dashboards and data sources, and analyze data to share insights.

We are a part of the Client Services Global Business Operations function and work with all levels of stakeholders, from executive leaders sharing insights with the C-Suite to customer-facing colleagues who rely on our assets to incorporate data into their daily responsibilities.

This specialist role makes data available from new sources, builds robust data models, creates and optimizes data enrichment pipelines, and provides engineering support to specific projects. You will partner with our Data Visualizers and Solution Designers to ensure that data needed by the business is available and accurate and to develop certified data sets. This technical lead and architect role is a force multiplier to our Visualizers, Analysts, and other data users across Client Services.

Responsibilities

• Design, develop, and maintain scalable data pipelines and systems.
• Monitor and troubleshoot data pipeline issues to ensure seamless data flow.
• Develop and enforce best practices for data management and governance.
• Mentor and guide junior data engineers, providing technical leadership and support
• Establish data processes and automation based on business and technology requirements, leveraging Visa’s supported data platforms and tools
• Deliver small to large data engineering and Machine learning projects either individually or as part of a project team
• Setup ML Ops pipelines to Productionalize ML models and setting up Gen AI pipelines
• Collaborate with cross-functional teams to understand data requirements and ensure data quality, with a focus on implementing data validation and data quality checks at various stages of the pipeline
• Provide expertise in data warehousing, ETL, and data modeling to support data-driven decision making, with a strong understanding of best practices in data pipeline design and performance optimization
• Extract and manipulate large datasets using standard tools such as Hadoop (Hive), Spark, Python (pandas, NumPy), Presto, and SQL
• Develop data solutions using Agile principles
• Provide ongoing production support
• Communicate complex concepts in a clear and effective manner
• Stay up to date with the latest data engineering trends and technologies to ensure the company's data infrastructure is always state-of-the-art, with an understanding of best practices in cloud-based data engineering

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.

Requirements

Basic Qualifications
• 5+ years of work experience with a bachelor’s degree in the STEM field.
• 4+ years of experience with SQL, Python, Hadoop, Spark, Hive, Airflow and MPP databases
Preferred Qualifications
• 7+ years of analytics experience with a focus on data engineering
• Experience with both traditional data warehousing tools and techniques (such as SSIS, ODI, and on-prem SQL Server, Oracle) as well as modern technologies (such as Hadoop, Denodo, Spark, Airflow, and Python), and a solid understanding of best practices in data engineering
• Advanced knowledge of SQL (e.g., understands subqueries, self-joining tables, stored procedures, can read an execution plan, SQL tuning, etc.)
• Solid understanding of best practices in data warehousing, ETL, data modeling, and data architecture.
• Strong understanding of best practices in data governance, data validation, and data quality checks
• Experience with NoSQL databases (e.g., MongoDB, Cassandra)
• Experience with cloud-based data warehousing and data pipeline management (AWS, GCP, Azure)
• Experience in Python, Spark, and exposure to scheduling tools like Tuber/Airflow is preferred.
• Able to create data dictionaries, setup and monitor data validation alerts, and execute periodic jobs to maintain data pipelines for completed projects
• Experience with visualization software (e.g., Tableau, QlikView, PowerBI) is a plus.
• A team player and collaborator, able to work well with a diverse group of individuals in a matrixed environment

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.