We are seeking a highly skilled Architect to lead the end-to-end migration of critical on-premises services and applications to a cloud-based infrastructure. The ideal candidate will have deep expertise in cloud architecture, Windows-based application migration, and experience working across multiple cloud platforms. This role requires close collaboration with cross-functional teams to ensure a seamless, secure, and efficient transition to the cloud. It would also be highly beneficial if the candidate has experience with multi-cloud systems to help design a resilient alarm reporting architecture that can automatically divert processing to an alternate cloud provider in the event of a service disruption.

Essential Duties And Responsibilities Architecture & Strategy

• Define and continuously evolve the data architecture across the Digital Products and Platforms
• Translate business and technical goals into scalable and resilient platform designs.
• Own and maintain architectural roadmaps, standards, and decision frameworks.
• Act as the bridge between architects, SME/Analysts, data engineers, and analytics teams to ensure alignment and compliance with platform standards.

Data Engineering & Platform Delivery

• Design and implement modern ELT/ETL pipelines using tools like Spark, Python, SQL, Scala, and cloud-native components (e.g., Databricks).
• Design and implement Data Modelling using Relational DB/NoSQL DB’s.
• Proven Hand-on experience in Databricks & Unity Catalog.
• Manage data ingestion from heterogeneous sources including ERP, CRM, IoT, and third-party APIs.
• Guide hands-on development of robust, reusable, and automated data flows.

Governance, Metadata, and Quality

• Implement and enforce data governance frameworks including data lineage, metadata management, and access controls.
• Develop data models (ERDs, dimensional and 3NF) and define canonical data representations.

Collaboration & Leadership

• Review solution designs and provide architectural guidance to engineering teams.
• Mentor technical staff while fostering best practices and continuous improvement.
• Collaborate with DevOps to embed CI/CD, version control, and environment automation across the data lifecycle.
• Continuously assess and improve platform reliability, scalability, performance, and cost-efficiency.

Qualifications REQUIRED:

• 12+ years of hands-on experience in data architecture and engineering delivery.
• Proven success in building modern data platforms on cloud (Azure, AWS, GCP).
• Deep knowledge of data lakehouse architectures (e.g., Databricks, Fabric).
• Proficiency with Python, SQL, Spark, and orchestration frameworks.
• Experience with ETL/ELT tools (e.g., Informatica, Talend, Fivetran) and containerization (Docker, Kubernetes).
• Strong background in Data Modeling (ERD, star/snowflake, canonical models).
• Familiarity with REST APIs, GraphQL, and event-driven design.
• Demonstrated experience integrating AI/ML and GenAI components into data platforms.
• Exposure to DataOps and DevOps practices for CI/CD and platform automation.

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