Director, VCA Data Engineering

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

Essential Functions

• Strong & progressive experience working with Global teams & Fortune 500 companies leading large scale implementations of data warehouses and data engineering solutions.

• Build and manage a team of talented data engineers with the ability to not only keep up with, but also pioneer, in this space.

• Experience implementing Large scale Big Data implementations for Large Organizations using Hybrid methodologies both On-prem Big Data Solutions and Cloud Implementations using Microsoft Azure or AWS

• Collaborate with and influence leadership so that your teams work directly impacts company strategy and direction.

• Exposure to Financial Services/ Payments data analytics and ETL development. Desirable exposure to Marketing, Authorization, Fraud & Chargeback Analytics.

• Experience in managing teams implementing ETL pipelines in Spark, Python, HIVE or SAS that process transaction and account level data and standardization of data pipelines.

• Experience working with technology and business teams on Data Governance, Data Quality and Data Architecture initiatives.

• Develop deep partnerships with engineering and product teams to deliver on major cross-functional measurements, testing.

• Communicate effectively to all levels of the organization, including executives.

• Find opportunities to create, automate and scale repeatable financial and statistical analysis for Visa Consulting and Analytics.

• Collaborate with Data Engineering teams in North America and other Global regions to production and maintenance of key data assets.

• Strong written, verbal, and interpersonal skills needed to effectively communicate technical insights and recommendations with business customers and leadership team.

Business skills and general qualities:

• Good business acumen to orient data analysis to business needs of clients.

• 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.

• Good 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.

• Demonstrated intellectual and analytical rigor, team oriented, energetic, collaborative, diplomatic, and flexible style.

• Intellectually curious and continuously striving to learn.

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

• 10 or more years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters/ MBA/JD/MD) or at least 3 years of work experience with a PhD

Preferred Qualifications

• 12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD
• Working knowledge of Hadoop ecosystem and associated technologies, (For e.g. Apache Spark, MLlib, GraphX, iPython, sci-kit,Pandas etc.)
• Experience in creating large scale data engineering pipelines, data-based decision-making and quantitative analysis.
• Experience with Visualization Tools like Tableau, Power BI, D3 and exposure to code version control systems (git).
• Experience – CICD/ Data Architectures/ Pipelines/ Quality /Code Management.
• Exposure to Data Science including Predictive Modeling
• Advanced experience in writing and optimizing efficient SQL queries with Python, Spark, Hive, Scala handling