Data Architect - Cloud, Big Data & AI Enablement

About the Role

We are seeking a highly experienced Data Architect to lead the design, development, and scaling of modern data platforms that serve as the foundation for enterprise AI and Gen AI initiatives. This role requires deep expertise in cloud technologies, big data ecosystems, and platforms like Databricks and Snowflake. You will act as a strategic technical advisor, helping organizations build robust, secure, and cost-optimized data architectures that drive business outcomes.

Key Responsibilities

• Architect and design end-to-end data platforms on cloud (Azure, AWS, or Google Cloud Platform) with a focus on scalability, performance, and cost-efficiency.
• Lead the implementation of data layers including ingestion, storage, processing, semantic, and consumption layers.
• Provide technical leadership on big data technologies (Spark, Delta Lake, Kafka, etc.) and modern data platforms (Databricks, Snowflake).
• Develop and optimize data pipelines using Scala or Python.
• Ensure data governance, security, IAM (Identity and Access Management), and compliance are embedded into the architecture from day one.
• Provide deployment support and drive cost optimization strategies across data workloads and cloud services.
• Support handling of unstructured data (e.g., documents, images, audio, video) to enable Gen AI use cases such as retrieval-augmented generation (RAG), document intelligence, and intelligent search.
• Collaborate with business and technical stakeholders to align data strategies with AI and analytics goals.
• Work closely with sales and pre-sales teams to position Data & AI solutions, contribute to proposals, and support client engagements.
• Stay current with emerging technologies and industry trends to continuously improve the data platform strategy.

Required Qualifications

• 8+ years of experience in data architecture, with a strong focus on cloud-native and big data solutions.
• Proven experience with Databricks, Snowflake, and cloud platforms (Azure, AWS, or Google Cloud Platform).
• Strong programming skills in Scala or Python for data engineering.
• Deep understanding of Spark, Delta Lake, and distributed data processing.
• Experience with IAM, data security, governance frameworks, and compliance standards (e.g., GDPR, HIPAA).
• Demonstrated experience working with unstructured data for Gen AI applications.
• Proven ability to support sales cycles, including technical presentations and solutioning.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Experience working in consulting or advisory roles with enterprise clients.
• Familiarity with AI/ML pipelines and how data architecture supports model development and deployment.
• Certifications in cloud platforms or data engineering (e.g., Azure Data Engineer, AWS Big Data Specialty).

Why Join Us?

• Be at the forefront of data-driven transformation and AI innovation.
• Work with a team of passionate experts in Data & AI.
• Influence strategic decisions and shape the future of enterprise data platforms.