Senior Data Architect
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Role details
Tech stack
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Requirements
7-12 years of experience in Data Engineering, Data Platforms, or Solution Architecture.
Experience in Python, PySpark, Spark SQL, and distributed data processing.
Experience working with Hadoop ecosystem and large-scale data platforms.
Hands-on expertise with Databricks Lakehouse and modern cloud-native architectures.
Experience with one or more cloud platforms: Azure, AWS, or Google Cloud Platform.
Collaborate closely with the Enterprise Architecture team to define target-state architectures and technology roadmaps.
Create and maintain Reference Architectures, Solution Blueprints, Design Patterns, and Architecture Standards.
Design scalable batch, streaming, and real-time data processing solutions.
Support AI/ML and Generative AI initiatives by building AI-ready data platforms and architectures.
Drive architecture reviews and ensure adherence to security, scalability, governance, and best practices.
Mentor engineering teams and provide technical leadership during solution design and implementation.
Strong communication and stakeholder management skills with the ability to influence architecture decisions.
Preferred Qualifications
Databricks Certification.
Azure/AWS Cloud Certification.
Prior experience working in Citibank consumer or wealth platform.
Exposure to Enterprise Architecture frameworks (TOGAF preferred).
Experience in Banking, Financial Services, or large-scale data modernization programs.
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