Director, Big Data Engineer, Global Data Science Center of Excellence, Visa
- Bengaluru, Karnataka, India
As the world's leader in digital payments technology, Visa's mission is to connect the world through the most creative, reliable and secure payment network - enabling individuals, businesses, and economies to thrive. Our advanced global processing network, VisaNet, provides secure and reliable payments around the world, and 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, and 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 and 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, 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.
The Director of Data Science is a lead Data Engineer role in the Central Europe, Middle East and Africa region (CEMEA) based out of Bangalore. We are looking for an expert with deep expertise in data warehousing and can build large-scale data processing systems by using the latest database technologies. This is a Pan-regional position and plays a critical role in enabling the data platforms through which Data Scientists, Analysts, and BI Users drive solutions for our Visa clients. Also, the role provides a bridge between our local end-users and our Visa Technology colleagues in San Francisco, influencing the development of our global data platforms whilst provisioning local tools and technologies as required. 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.
- Design local modifications to our global data architecture, including new tools and technologies where necessary to meet regional use-cases
- Provide direction to the development of bespoke, client-specific data sandboxes
- Create and maintain optimal data pipeline architecture(s), based on our Global Technology Stack
- Identify, design, and implement internal process improvements to provide greater scalability to our existing client solutions
- Develop custom-built packages and “glue code” to support the needs of Data Scientists across the region
- Work with broader business stakeholders to assist clients and consultants with their data and infrastructure needs
Work with Visa’s Global Technology team to leverage our existing architecture to best effect, whilst identifying new and complementary tools and technology that will better enable our local solutions; serve as key contact and subject matter expert in working with the Visa Technology functions around the world (both global and regional)
Design sandbox architecture
Provide SME support to the design and build of client-specific data sandboxes that may leverage the advantages of cloud technologies whilst ensuring strong security and privacy controls
Build data pipelines
Build and operate stable, scalable data pipelines that cleanse, structure and integrate data sets into accessible formats for Data Scientists and other end-users, ensuring that testing and monitoring functions are performed appropriately
Supporting external clients’ data architecture
Provide Data Engineering expertise support to Visa’s select top-level clients, advising on how to implement, acquire, and improve their existing and planned data solutions. Such solutions can involve complex data integration from various sources (from an internal data warehouse, applicable VisaNet transaction data or third-party data) within the constraints of the client’s legal and regulatory limitations.
Implement for scale
Co-create and contribute to the design and deployment of scalable, high volume and real-time data solutions (dashboards, data feeds, and algorithms) running in production systems to ensure optimal functioning and sustainability of solutions built
Support Data Scientists
Provide advisory and hands-on support to Data Scientists by providing quality assurance to teams writing poor-quality data queries on our queue, and developing custom-built packages and “glue code” that take algorithms into production
Serve as subject matter expert
Provide support and advisory assistance to business stakeholders (client relationship managers, consultants, and other internal stakeholders) in framing potential use-cases, client engagements, and internal initiatives
- 8 - 10 years' application development and support experience.
- Deep knowledge of distributed data architecture, commonly-used BI tools, and approaches/packages deployed for machine learning build
- Experience creating production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems.
- Experience in machine learning algorithm design, feature engineering, validation, prediction, recommendation, and measurement.
- Experience with complex, high volume, multi-dimensional data, as well as machine learning models based on unstructured, structured, and streaming datasets.
- Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant
- Experience planning, organising, and managing multiple large projects with diverse cross-functional teams
- Demonstrated ability to incorporate new techniques to solve business problems
- Demonstrated resource planning and delivery skills
- Post Graduate Degree in Information Technology
- Qualification in Computer Science or Engineering ideal.
- Certification in Hadoop (Cloudera or Hortonworks) and Apache Spark.
- Working knowledge of Hadoop ecosystem and associated technologies, e.g., Apache Spark, MLlib, GraphX, iPython, sci-kit, and Pandas
- Advanced experience in writing and optimizing efficient SQL queries and Python scripts; Scala and C++ experience is ideal
- Deliver results within committed scope, timeline and budget
- Very strong people/project management skills and experience
- Ability to travel within CEMEA on short notice
- Results-oriented with strong problem solving skills and demonstrated intellectual and analytical rigor
- Good business acumen with a track record in solving business problems through data-driven quantitative methodologies. Experience in payment, retail banking, or retail merchant industries is preferred
- Team oriented, collaborative, diplomatic, and flexible style
- Very detailed oriented, is expected to ensure highest level of quality/rigor in reports and data analysis
- Proven skills in translating analytics output to actionable recommendations and delivery
- Experience in presenting ideas and analysis to stakeholders whilst tailoring data-driven results to various audience levels
- Exhibits intellectual curiosity and a desire for continuous learning
- Exhibits intellectual curiosity and a desire for continuous learning
- Demonstrates integrity, maturity and a constructive approach to business challenges
- Role model for the organization and implementing core Visa Values
- Respect for the Individuals at all levels in the workplace
- Strive for Excellence and extraordinary results
- Use sound insights and judgments to make informed decisions in line with business strategy and needs
- Leadership skills include an ability to allocate tasks and resources across multiple lines of businesses and geographies. Leadership extends to ability to influence senior management within and outside Analytics groups
- Ability to successfully persuade/influence internal stakeholders for building best-in-class solutions
- Change management leadership