As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable & secure payment network - enabling individuals, businesses, & economies to thrive. Our advanced global processing network, VisaNet, provides secure & reliable payments around the world, & is capable of handling more than 65,000 transaction messages a second. The company's dedication to innovation drives the rapid growth of connected commerce on any device, & fuels the dream of a cashless future for everyone, everywhere. As the world moves from analog to digital, Visa is applying our brand, products, people, network & scale to reshape the future of commerce.
At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, & be part of an inclusive & diverse workplace. We are a global team of disruptors, trailblazers, innovators & risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, & doing meaningful work that brings financial literacy & digital commerce to millions of unbanked & underserved consumers.
You're an Individual. We're the team for you. Together, let's transform the way the world pays.
To ensure that Visa's payment technology is truly available to everyone, everywhere requires the success of our key bank or merchant partners & internal business units. The Global Data Science group supports these partners by using our extraordinarily rich data set that spans more than 3 billion cards globally & captures more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science & various groups at Visa. To support our rapidly growing group we are looking for data engineers who are equally passionate about the opportunity to use Visa's rich data to tackle meaningful business problems. This position will be part of Data Engineering & Technology function in building & maintaining global data assets & issuer solutions. We are looking expertise in data warehousing & building large-scale data processing systems by using the latest database technologies. The Data Engineer takes responsibility for building & running data pipelines, designing our local data warehouse & data frameworks, & catering for different data presentation techniques. The position is based at Visa's offices in Bangalore, India.
- Execute & manage large scale ETL processes to support development & publishing of reports, Datamart's & predictive models.
- Build ETL pipelines in Spark, Python, HIVE or SAS that process transaction & account level data & standardize data fields across various data sources
- Build & maintain high performing ETL processes, including data quality & testing aligned across technology, internal reporting & other functional teams
- Create data dictionaries, setup/monitor data validation alerts & execute periodic jobs like performance dashboards, predictive models scoring for client's deliverables
- Define & build technical/data documentation & experience with code version control systems (e.g. git)
- Ensure data accuracy, integrity & consistency. Develop self-service reporting tools like Tableau or Power BI with KPIs & facilitate Visa Consulting engagements including data exchange
- Find opportunities to create, automate & scale repeatable financial & statistical analysis for Visa Consulting & Analytics.
- Collaborate with Data Engineering teams in North America & other Global regions to production & maintenance of key data assets.
- 2 - 4+ yrs. work experience with a Bachelor's Degree or 2+ years of work experience with a Master's or Advanced Degree in an analytical field such as computer science, statistics, finance, economics or relevant area.
- Working knowledge of Hadoop ecosystem & associated technologies, (For e.g. Apache Spark, MLlib, GraphX, iPython, sci-kit,Pandas etc.)
- 3-5+ yrs. work experience with a Bachelor's Degree or 3+ years of work experience with a Master's or Advanced Degree in an analytical field such as Computer Science, Statistics, Finance, Economics or relevant area.
- Strong experience in creating Large scale data engineering pipelines, data-based decision-making & quantitative analysis.
- Advanced experience in writing & optimizing efficient SQL queries with Python, Hive, Scala handling Large Data Sets in Big-Data Environments.
- Experience with complex, high volume, multi-dimensional data, as well as machine learning models based on unstructured, structured, & streaming datasets.
- Experience with SQL for extracting, aggregating & processing big data Pipelines using Hadoop, EMR & NoSQL Databases.
- Experience with Visualization Tools like Tableau, Power BI, D3 & exposure to code version control systems (git).
- Experience creating/supporting production software/systems & a proven track record of identifying & resolving performance bottlenecks for production systems.
- Experience with Unix/Shell or Python scripting & exposure to Scheduling tools like Oozie & Airflow.
Exposure to stream-processing systems like Apache Storm, Spark-Streaming.