About Us

Help us enable everyone on the planet to gain access to the global economy by being the best way to pay and be paid.

Size: 10000+ employees
Industry: Technology, Fintech, Engineering, Information Technology

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Company Description

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world.

Progress starts with you.

Job Description

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.

Qualifications

8+ years of hands-on data engineering experience with a Bachelor's degree, or 6+ years with a Master's degree in Computer Science, Engineering, Statistics, or related technical field

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Proven track record of building and leading complex data engineering projects at scale Must-Have Technical Skills:Core Data Engineering Expertise:Expert proficiency in Python and Scala/Java for building production data systems Deep hands-on experience with Apache Spark (Spark SQL, Data Frames, Streaming) including performance tuning and optimization Strong expertise in Hadoop ecosystem: HDFS, Hive, HBase, YARNProduction experience with Kafka for building event-driven and streaming architectures Advanced SQL skills with experience in both RDBMS and NoSQL databases (Cassandra, MongoDB, Redis)Proven experience designing and deploying large-scale ETL/ELT pipelines processing terabytes of data Strong AWS/Azure experience: S3, EMR, EC2, Lambda, Glue, Redshift, SageMaker Solid understanding of data modeling, partitioning strategies, and distributed systems optimizationDevOps & Infrastructure:Experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions)Hands-on experience with Docker and Kubernetes for containerization and orchestration Proficiency with workflow orchestration tools like Airflow, Prefect, or Control-MExperience with infrastructure as code and automationMLOps & AI Infrastructure:Experience building feature engineering pipelines and feature stores Understanding of MLOps workflows: model deployment, versioning, monitoring, and automation Experience building data pipelines that support ML/AI workloads Familiarity with model lifecycle management and productionization Preferred Skills:Advanced Data Engineering:Experience with real-time processing frameworks (Flink, Spark Streaming, Kafka Streams)Familiarity with modern data platforms (Databricks, Snowflake)Experience with data quality frameworks and observability tools (Great Expectations, Datadog, Prometheus)Knowledge of DR/HA architectures and reliability engineering Multi-cloud experience (Azure, GCP)Understanding of data governance, security, and complianceAI/GenAI Infrastructure:Experience with vector databases (Pinecone, Weaviate, Milvus, ChromaDB, FAISS)Understanding of RAG (Retrieval-Augmented Generation) system architectures Familiarity with Model Context Protocol (MCP) for LLM integrations Experience with embeddings generation and semantic search pipelines Exposure to model serving frameworks (Tensor Flow Serving, Triton, Sage Maker endpoints)Knowledge of cloud AI services (AWS Bedrock, Azure OpenAI, Vertex AI)Experience with LLM orchestration frameworks (Lang Chain, Llama Index)What Makes You Stand Out:Strong architectural thinking with ability to design systems for scale, reliability, and maintainability Proven ability to drive technical initiatives independently with minimal supervision Deep problem-solving skills and comfort navigating ambiguity in complex technical environments Excellent communication and stakeholder management abilities Passion for mentoring and elevating engineering teams Curiosity and adaptability to stay ahead of emerging technologies in data engineering and AI/ML

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Client-provided location(s): Bangalore, India

Job ID: 3fc7fa3b-cf22-4ed6-aab4-7259bffab6d1

Employment Type: OTHER

Posted: 2026-01-20T06:02:38
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Perks and Benefits

Health and Wellness

• Long-Term Disability
• HSA With Employer Contribution
• On-Site Gym
• Health Insurance
• Dental Insurance
• Vision Insurance
• Life Insurance
• Short-Term Disability
• Health Reimbursement Account
• Mental Health Benefits
• Virtual Fitness Classes
• HSA

Parental Benefits

• Fertility Benefits
• Family Support Resources
• Birth Parent or Maternity Leave
• Non-Birth Parent or Paternity Leave

Work Flexibility

• Flexible Work Hours
• Remote Work Opportunities
• Hybrid Work Opportunities

Office Life and Perks

• Commuter Benefits Program
• Company Outings
• On-Site Cafeteria
• Holiday Events
• Happy Hours
• Casual Dress

Vacation and Time Off

• Paid Holidays
• Paid Vacation
• Volunteer Time Off
• Summer Fridays
• Leave of Absence
• Personal/Sick Days

Financial and Retirement

• 401(K)
• Relocation Assistance
• Performance Bonus
• Stock Purchase Program
• Company Equity
• 401(K) With Company Matching
• Financial Counseling

Professional Development

• Shadowing Opportunities
• Access to Online Courses
• Promote From Within
• Learning and Development Stipend
• Tuition Reimbursement
• Mentor Program
• Leadership Training Program
• Associate or Rotational Training Program
• Lunch and Learns
• Internship Program
• Professional Coaching

Diversity and Inclusion

• Diversity, Equity, and Inclusion Program
• Employee Resource Groups (ERG)

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