Senior Data Analytics Architect

Senior Data Analytics Architect

We are seeking an experienced Senior Data Analytics Architect with over 15 years of expertise in designing and delivering enterprise-scale data, analytics, and AI-enabled solutions. This role will lead the architecture, design, and implementation of modern data analytics platforms on Google Cloud Platform (GCP), enabling advanced analytics, data warehousing, and artificial intelligence use cases.

The Senior Data Analytics Architect will work closely with Product teams, development and production support teams, business users, and data consumers to ensure data solutions are scalable, reliable, secure, and aligned with business objectives.

Key Responsibilities

• Define and own the enterprise data and analytics architecture, aligning with business strategy and long-term analytics roadmap.
• Architect end-to-end data warehousing, analytics, and AI-ready data platforms.
• Design logical, physical, and analytical data models to support reporting, dashboards, advanced analytics, and AI/ML workloads.
• Establish architecture standards, design patterns, and best practices for analytics and data platforms.
• Architect data ingestion, streaming, and batch pipelines using Informatica IDMC, Pub/Sub, and Cloud Composer.
• Design and implement cloud-native analytics solutions on GCP, with a strong focus on Big Query.
• Architect scalable data warehouses and analytics layers optimized for high-performance querying.
• Design and oversee data ingestion, transformation, and orchestration pipelines using Informatica IDMC.
• Enable analytics and AI use cases by ensuring data is well-structured, governed, and accessible.
• Support advanced analytics and AI initiatives by designing data architectures optimized for machine learning and data science workloads.
• Collaborate with analytics and AI teams to ensure data availability, quality, and performance.
• Ensure the data platform supports exploratory analytics, predictive modeling, and AI-driven insights.
• Provide hands-on architectural guidance to development teams throughout the development lifecycle.
• Review SQL, Python code, and data pipelines for performance, scalability, and reliability.
• Support production environments, including monitoring and troubleshooting data pipeline failures, performance tuning and optimization, root cause analysis and issue resolution.
• Partner with Product teams to translate product and analytics requirements into robust data solutions.
• Work closely with business users and data consumers to understand reporting, analytics, and insight needs.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
• Act as a trusted advisor for data, analytics, and AI capabilities.
• Define and enforce data governance, data quality, and metadata management standards.
• Ensure compliance with enterprise security, privacy, and regulatory requirements.
• Promote best practices for data lineage, auditing, and access control across analytics platforms.

Required Skills & Qualifications

• 15+ years of experience in Data Architecture, Data Analytics Architecture, and Data Warehousing.
• Proven experience delivering enterprise-scale data and analytics solutions.
• Strong background in supporting both development and production environments.
• Strong hands-on experience with GCP, including Big Query, Pub/Sub, and Cloud Composer.
• Strong experience with Big Query (analytics design, optimization, cost, and performance tuning) and Informatica Intelligent Data Management Cloud (IDMC).
• Advanced proficiency in Complex SQL (query tuning, analytical functions).
• Strong and experienced Python skills for data processing, automation, and analytics support.
• Extensive experience with Data Warehousing concepts, including dimensional and analytical data modeling.
• Experience designing data platforms for data analytics and AI/ML workloads.
• Excellent communication and stakeholder management skills.
• Ability to translate business requirements into technical architecture.
• Strong analytical, problem-solving, and decision-making abilities.
• Proven ability to work across cross-functional and geographically distributed teams.

Required Qualifications

• Experience working in large enterprise or highly regulated environments.
• Exposure to BI tools, analytics platforms, and data science ecosystems.
• Familiarity with DevOps, CI/CD pipelines, and production monitoring for data platforms.
• Experience with data governance, cataloging, and quality tools.