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Vistaar
@uttamkasundra
Level 1
AIML, Feature Engineer, Distributed Streaming and Computing, Observability
Índia
Inglês
Sobre mim
Data Engineering Architect with 13 years of experience in designing, building, scaling and Observing enterprise-grade Big Data and AI/ML platforms across fintech, digital advertising, and analytics domains. Expert in end-to-end architecture, including Lakehouse and warehouse , streaming/batch pipelines, feature engineering, and microservices. Delivered high-throughput, low-latency, secure solutions while ensuring governance, compliance (PCI-DSS, GDPR/DPDP) and operational excellence.
Skilled in AWS, GCP, CDP/CDE, Spark, Kafka, Big Query, Cassandra, Datastore, Airflow, Docker, Terraform.
Habilidades
Vistaar
US$ 50/hora
offline •
Conheça meus serviços
Suporte Técnico
I will setup datadog observability for infra
Consultoria em Engenharia de Dados
I will build spark etl data pipeline
Quer trabalhar com remuneração por hora?
Diga a Vistaar o que você precisa.
US$ 50
/
horaPortfólio
Experiência profissional
Lead Data Engineer
Global payment network (Fortune 500) • Período integral
Jan 2020 - Present • 6 yrs 6 mos
Delivered advanced data engineering and analytical capabilities supporting a global payment network, enabling scalable and secure financial data processing. Led end-to-end solution design, including product requirement analysis and integration data flows across complex upstream and downstream systems. Designed and developed high-quality batch and real-time Spark applications with strong emphasis on maintainability, security, and compliance standards. Architected and orchestrated large-scale deployments, job scheduling, and data lake frameworks, including a rule-based outbound feed generation engine supporting multiple sources, transformations, and targets. Worked within cross-functional agile teams, owning data lake modeling (MongoDB), development standards, and delivery quality for enterprise prepaid management platforms.
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paulfierro147
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Vistaar and Uttam Patel are great technical resources for scalable cloud-based systems. They can support complex projects and help clarify problems and their corresponding solutions. We will be using them going forward.
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