Job Description
Position Summary
This Director Data Engineer role in the CEMEA (Central Europe, Middle East and Africa) region is primarily responsible for establishing frameworks for Machine Learning productionization (MLOps) and streaming model deployment. We are looking for an expert with deep expertise who can build end-to-end model deployment pipelines using the latest tools, platforms, and technologies. This is a Pan-regional position supporting all of CEMEA that plays a critical role in enabling the Data Science team to deliver solutions for our Visa clients. The role also provides a bridge between our local end-users and our Visa Technology colleagues in San Francisco, influencing the development of standardized processes whilst provisioning local tools and technologies as required. The Data Engineer takes responsibility for building and running data pipelines, launching models in production, and maintaining continuously-running models under SLA’s as defined by client end-users.
Principal Responsibilities
Design and implement frameworks for streaming machine learning model productionization, working closely with Data Scientists, end-users, and clients
Advise clients on suggested processes, tools, and platforms to manage end-to-end model productionization, working with available platforms and systems within client environments
Design local modifications to our global Visa 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 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
Professional Experience
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 in Python and/or Scala, 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
Qualifications
Post Graduate Degree in Information Technology
Qualification in Computer Science or Engineering ideal.
Certification in Hadoop (Cloudera or Hortonworks) and Apache Spark.
Experience in developing production systems, with software engineering governance practices in place e.g, unit testing frameworks, CI/CD and scheduling technologies
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
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