Data Engineer, VCA Data Engineering
- Full-time
- Job Family Group: Product Development
Company Description
At Visa, your individuality fits right in. Working here gives you an opportunity to impact the world, invest in your career growth, and be part of an inclusive and diverse workplace. We are a global team of disruptors, trailblazers, innovators and risk-takers who are helping drive economic growth in even the most remote parts of the world, creatively moving the industry forward, and doing meaningful work that brings financial literacy and digital commerce to millions of unbanked and underserved consumers.
You're an Individual. We're the team for you. Together, let's transform the way the world pays.
Job Description
To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our key bank or merchant partners and 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 and 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 and 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 VCA (Visa Consulting & Analytics) Data Engineering and Technology function in building and maintaining global data assets and issuer solutions. We are looking expertise in data warehousing and building large-scale data processing systems by using the latest database technologies. The Data Engineer takes responsibility for building and running data pipelines, designing our local data warehouse and data frameworks, and catering for different data presentation techniques. The position is based at Visa's offices in Bangalore, India.
Essential Functions
Execute and manage large scale ETL processes to support development and publishing of reports, Datamart’s and predictive models.
Build ETL pipelines in Spark, Python, HIVE or SAS that process transaction and account level data and standardize data fields across various data sources
Build and maintain high performing ETL processes, including data quality and testing aligned across technology, internal reporting and other functional teams
Create data dictionaries, setup/monitor data validation alerts and execute periodic jobs like performance dashboards, predictive models scoring for client’s deliverables
Define and build technical/data documentation and experience with code version control systems (e.g. git)
Ensure data accuracy, integrity and consistency. Develop self-service reporting tools like Tableau or Power BI with KPIs and facilitate Visa Consulting engagements including data exchange
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.
Qualifications
Basic Qualifications
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 and associated technologies, (For e.g. Apache Spark, MLlib, GraphX, iPython, sci-kit,Pandas etc.)
Preferred Qualifications
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.
Technical skills:
Strong 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).
Advanced experience in writing and 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, and streaming datasets.
Experience with SQL for extracting, aggregating and processing big data Pipelines using Hadoop, EMR & NoSQL Databases.
Experience creating/supporting production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems.
Experience with Unix/Shell or Python scripting and exposure to Scheduling tools like Oozie and Airflow.
Exposure to stream-processing systems like Apache Storm, Spark-Streaming.