We are seeking an experienced Manager Data & AI Engineer to join our CEMEA team. This is a Staff-level individual contributor role for someone who thrives on solving complex technical challenges, architecting scalable data platforms, and driving engineering excellence. You'll lead critical data engineering initiatives, mentor talented engineers, and build the data infrastructure that powers insights and AI-driven solutions for Visa's global clients.
What You'll Do:
Data Platform Architecture & Development:
- Design and build enterprise-scale data platforms using modern big data technologies including Spark, Hadoop, Kafka, and cloud-native services.
- Architect robust, scalable data pipelines that process petabytes of data for batch, streaming, and real-time analytics
- Drive technical decisions on architecture, tooling, and engineering practices that impact multiple projects and teams
- Establish and enforce engineering standards, best practices, and code quality across data engineering initiatives
Build Production-Grade Data Pipelines:
- Develop and optimize large-scale ETL/ELT pipelines for data ingestion, transformation, quality assurance, and feature engineering
- Implement streaming data pipelines using Kafka and Spark Streaming for real-time analytics and decision-making
- Design data models, partitioning strategies, and optimization techniques for distributed systems
- Ensure data quality, reliability, and observability across all data workflows
Enable AI/ML & Advanced Analytics:
- Build data infrastructure that supports AI/ML workloads including feature stores, training pipelines, and model serving infrastructure
- Collaborate with data scientists to productionize machine learning models through robust MLOps practices
- Design and implement data pipelines for GenAI applications including embeddings generation, vector storage, and retrieval systems
- Support deployment of AI/ML models with scalable inference pipelines and monitoring
Drive Cloud Infrastructure & DevOps Excellence:
- Manage and optimize AWS/Azure cloud infrastructure (S3, EMR, EC2, Lambda, Glue, Redshift, SageMaker)
- Build CI/CD pipelines and automate deployments using Jenkins, Git, Docker, and Kubernetes
- Implement workflow orchestration using Airflow, Prefect, or Control-M
- Design for high availability, disaster recovery, and system reliability
Technical Leadership & Collaboration:
- Mentor junior data engineers, fostering a culture of continuous learning and innovation
- Code reviews and technical discussions to elevate team capabilities
- Partner with product managers, data scientists, and business stakeholders to translate requirements into technical solutions
- Stay current with emerging technologies and drive adoption of best practices in data engineering and AI/ML infrastructure
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.