Data Architect

Must Have Technical/Functional Skills Strong hands-on expertise with modern data platforms and architectures, including ETL/ELT, streaming, and event-driven patterns. Proven ability to build/guide scalable data pipelines, data models, and integration patterns across heterogeneous sources and platforms. Experience implementing AI/GenAI solutions in the enterprise contexts. Solid engineering fundamentals, production readiness mindset. Working knowledge of data governance and cataloging tools/processes (e.g., Collibra/Alation/Informatica) and ability to embed governance into architecture. Google Cloud exposure (preferred strong): and integration with data services (e.g., BigQuery/Cloud Storage) and scalable runtime options. Roles & Responsibilities 15+ years of experience in Data Solution Architecture with experience in Cloud Data Management Platforms. At least 3-4 years of work experience in data management disciplines including data integration, data modeling, optimization, data lifecycle management and data quality. Strong hands on experience with modern data platforms and architectures. Deep understanding of ETL/ELT, streaming, and event driven patterns. Proficiency in SQL, Python, and big data query optimization. Develop data models, pipelines, APIs, and integration strategies across multiple data sources and platforms. Ensure architectures support analytics, AI/ML, and business intelligence use cases. Promoting best practices in coding, design, and performance optimization. Familiarity with data governance tools (Collibra, Alation, Informatica etc.). Skilled working across multiple deployment environments including cloud, on-premises and hybrid. Excellent communication and stakeholder management skills.

Salary Range: $100,000 to $130,000 per year