Principal Data Architect
Access SystemsSalary not specified
Full Time
Expert & Leadership (9+ years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Payments, FinTech, TechnologyIndustries
Requirements
- Expertise in designing and implementing large-scale, distributed data systems integrating Hadoop, Apache Spark, Databricks, and cloud-native services (AWS/Azure)
- Experience developing robust ETL and streaming pipelines for large volumes of transactional and behavioral data supporting machine learning and analytics
- Proficiency in data warehouse modernization, ensuring scalability, data quality, lineage, and governance
- Knowledge of AI/ML data infrastructure, including data models for ML pipelines, feature engineering, model training, and frameworks like LangChain, LangGraph, and MCP
- Ability to design reusable frameworks for extracting, transforming, and surfacing insights from structured, semi-structured, and unstructured data (e.g., JSON, logs, events)
- Experience leading POCs for emerging technologies (e.g., Delta Lake, Iceberg, Kafka, Arrow) and translating to production systems
- Familiarity with security practices, including end-to-end data encryption, secure access, and compliance with global data privacy standards
- Strong leadership and mentorship skills for coaching junior engineers and data scientists
- Ability to collaborate with global teams across India and the US, ensuring consistent design standards and architecture alignment
- Experience working directly with product owners and cross-functional teams (AI/ML, product, analytics, platform)
Responsibilities
- Architect and lead data solutions: Design and implement large-scale, distributed data systems integrating Hadoop, Apache Spark, Databricks, and cloud-native (AWS/Azure) services
- Build enterprise data pipelines: Develop robust ETL and streaming pipelines handling large volumes of transactional and behavioral data for ML and analytics workloads
- Lead data warehouse modernization of Hadoop-based systems, ensuring scalability, data quality, lineage, and governance
- Collaborate with AI scientists to deliver data models optimized for ML pipelines, feature engineering, and model training
- Design and build reusable frameworks to extract, transform, and surface insights from structured, semi-structured, and unstructured data sources
- Lead POC initiatives to evaluate emerging technologies and translate findings into scalable production systems
- Ensure security and compliance by collaborating with InfoSec on data encryption, secure access, and privacy standards
- Mentor and coach junior engineers and data scientists, fostering technical excellence, collaboration, and innovation
- Work closely with global data engineering teams across India and the US for consistent design, architecture decisions, and high-quality delivery
- Partner with product management, AI, and platform teams to align engineering initiatives with business goals and data strategy
- Work directly with product owners
Skills
Data Engineering
AI/ML
Hadoop
AWS
Azure
Data Pipelines
Distributed Systems
Cyber Security
Visa
Global digital payment network provider
About Visa
Visa operates a global digital payment network that facilitates electronic payments for millions of people daily. The company connects consumers, businesses, financial institutions, and governments, allowing them to make transactions using Visa cards. Each time a card is used, Visa earns money through transaction, service, and data processing fees. Unlike many competitors, Visa focuses on expanding access to financial services for underserved communities and supporting local economies. The company's goal is to promote financial inclusivity and drive sustainable commerce, ensuring that more people can participate in the global economy.
San Francisco, CaliforniaHeadquarters
1958Year Founded
$55.8MTotal Funding
ANGEL_INDIVIDUALCompany Stage
Fintech, Financial ServicesIndustries
10,001+Employees
Benefits
Health Insurance.
Life Insurance.
Dental Insurance.
Disability Insurance.
Accidental Death & Dismemberment Insurance.
Risks
CBDCs could reduce reliance on Visa's payment network.
'Buy Now, Pay Later' services may decrease traditional credit card transactions.
Fintech startups offering zero-fee transactions could pressure Visa's revenue model.
Differentiation
Visa operates a global digital payment network connecting millions daily.
The company focuses on financial inclusivity and sustainability in its operations.
Visa collaborates with central banks on Central Bank Digital Currencies (CBDCs).
Upsides
Visa's partnership with fintechs enhances cross-border payment solutions.
Adoption of blockchain technology could revolutionize digital payments.
AI-driven fraud detection systems are reducing fraudulent activities.
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