Manager, Data Engineering

Visa•Austin, TX

2h•Hybrid

About The Position

Payment Ecosystem Risk and Controls is a Global Risk group that is tasked with the protect the Global Payment Ecosystem against threats and abuse by transforming risk controls, leveraging intelligence-driven solutions, and upholding Visa’s Rules and Standards. This is achieved through the deployment of risk quality control and/or compliance programs. The programs are deployed through Visa Rules and additional client guidelines and Visa performs quality control leveraging proprietary tools, specialized third party vendors, regional risk teams, and other stakeholders. The team also works with internal and external stakeholders to further its charter and initiatives. Essential Functions: This role is responsible for executing on analytics and reporting initiatives which deliver data-driven insights to internal and external stakeholders, including Visa executives, issuing banks, acquirers, processors and merchants regulators. Success in this role requires strong analytical and data story telling skills for both executive and regional delivery. By collaborating with client-facing teams and functional leaders, you will provide data and insights that deliver mutual, tangible value to Visa and its clients through improved payment security. You will work on the innermost of Visa’s core data and system and contribute to the development of industry-leading capabilities to protect Visa and our clients from emerging payment threats. You must be able to work both independently and as part of a team to deliver on a dynamic set of needs in a fast-paced environment. Specific responsibilities include:

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
Proficiency in data analysis and utilization of various data environments and tools.
High-level understanding of manipulating data from a variety of sources.
Big data experience (Hadoop, Hive, Spark), data visualization experience (Tableau, Power BI) and/or SQL experience are critical skills – this role is about both doing and delivering.
Strong verbal, written, motivational and interpersonal skills are required.
Good communication, presentation, and interpersonal skills.
Working knowledge of scripting languages like Python, with a foundational understanding of machine learning concepts.
A collaborative mindset with the ability to work effectively within cross-functional teams.
Strong analytical and problem-solving skills with a passion for data-driven decision making.

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

Perform Program Operations function - analyze ecosystem compliance program design through data, assess impact with data simulations, solve data refute cases within defined SLAs
Perform in-depth analysis and deliver insights on various regional & global priorities
Contribute to a high performing culture that becomes the benchmark for excellence at Visa
Define product requirements and roadmaps based on business needs, network rules & requirements, and industry best practices
Ensure data driven decision making is a priority for clients, colleagues, and other internal and external stakeholders
Knowledge of Visa’s products, services, and client engagement strategies.
Analyze large datasets to identify trends, patterns, and key performance indicators .
Develop and maintain Hive & Python (and spark) queries to extract, transform, and load data from various sources, including Hadoop and cloud-based platforms.
Develop compelling data visualizations using Power BI and Tableau to communicate insights seamlessly to PMs/ Engineering and leadership.
Partner with cross-functional teams (operations, technology, marketers) to translate data into actionable insights and drive strategic decision-making.
Effectively communicate analytical findings to stakeholders at all levels, both verbally and in writing.