Data Scientist

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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 minimized. We govern Client Services operational data and metrics, create easily usable dashboards and data sources, and analyze data to share insights.

We are part of the Client Services Global Business Operations function and collaborate 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 involves making data available from new sources, building robust data models, creating and optimizing data enrichment pipelines, and providing engineering support for specific projects. You will partner with Data Visualizers and Solution Designers to ensure data needed by the business is available and accurate, and to develop certified data sets. This technical lead and architect role amplifies the efforts of Visualizers, Analysts, and other data users across Client Services.

1. Design, develop, and maintain scalable data pipelines and systems.
2. Monitor and troubleshoot data pipeline issues to ensure seamless data flow.
3. Establish data processes and automation based on business and technology requirements, leveraging Visa-supported data platforms and tools.
4. Deliver small to large data engineering and Machine Learning projects, either individually or as part of a team.
5. Set up ML Ops pipelines to productionize ML models and establish Gen AI pipelines.
6. Collaborate with cross-functional teams to understand data requirements and ensure data quality, implementing validation and quality checks at various pipeline stages.
7. Provide expertise in data warehousing, ETL, and data modeling to support data-driven decision-making, following best practices in pipeline design and performance.
8. Extract and manipulate large datasets using tools like Hadoop (Hive), Spark, Python (pandas, NumPy), Presto, and SQL.
9. Develop data solutions using Agile methodologies.
10. Provide ongoing production support.
11. Communicate complex concepts clearly and effectively.
12. Stay updated with the latest trends and technologies in data engineering to ensure state-of-the-art infrastructure, including cloud-based solutions.

This is a remote position. Remote work does not require duties to be performed within proximity of a Visa office, but may require presence at a Visa office with prior notice.

• At least 2 years of work experience with a Bachelor's Degree or higher (e.g., Master's, MBA, JD, MD, PhD).

• Over 3 years of work experience with a Bachelor's Degree or more than 2 years with an Advanced Degree.
• Over 3 years of experience in STEM fields.
• Strong experience with SQL, Python, Hadoop, Spark, Hive, Airflow, and MPP databases.
• More than 5 years of analytics experience focusing on Data Engineering and AI.
• Experience with both traditional data warehousing and modern technologies like Hadoop, Denodo, Spark, Airflow, and Python.
• Advanced SQL skills, including subqueries, self-joins, stored procedures, execution plan analysis, and tuning.
• Solid understanding of data warehousing, ETL, data modeling, and architecture best practices.
• Experience with NoSQL databases such as MongoDB and Cassandra.
• Experience with cloud data warehousing and pipeline management (AWS, GCP, Azure).
• Proficiency in Python, Spark, and scheduling tools like Airflow.
• Ability to create data dictionaries, monitor validation alerts, and execute periodic jobs.
• Experience with visualization tools like Tableau, QlikView, or PowerBI is a plus.
• Strong collaborator and team player, capable of working in a diverse, matrixed environment.

Additional information,

• Job tags: python, data modeling, sql, hadoop