Lead Data Architect

Job Summary We are looking for a highly experienced Lead Data Architect to design, implement, and govern enterprise data architecture strategies. The candidate will lead the design of scalable data platforms, data models, integration frameworks, and governance processes to support analytics, AI, and business intelligence initiatives. This role requires strong leadership, deep technical expertise in modern data platforms, and the ability to collaborate with business and technology stakeholders to deliver data-driven solutions. Key Responsibilities 1. Enterprise Data Architecture • Define and maintain enterprise data architecture vision, standards, and best practices. • Design scalable data platforms, data lakes, and data warehouses. • Develop conceptual, logical, and physical data models for enterprise systems. • Establish data architecture aligned with business strategy. 1. Data Platform & Engineering Leadership • Architect modern data ecosystems using technologies such as • Apache Spark • Snowflake • Databricks • Apache Kafka • Design and optimize ETL/ELT pipelines and streaming architectures. • Guide teams in implementing data lakes, lakehouse architectures, and real-time analytics. 1. Cloud Data Architecture • Lead cloud-based data platform implementations on: • Amazon Web Services • Microsoft Azure • Google Cloud Platform • Architect cloud-native data pipelines, storage, and analytics solutions. • Ensure scalability, performance, security, and cost optimization. 1. Data Governance & Quality • Establish enterprise data governance frameworks, metadata management, and data cataloging. • Implement data quality, lineage, and compliance practices. • Ensure compliance with standards such as GDPR and HIPAA when applicable. 1. Leadership & Stakeholder Management • Lead and mentor data architects, data engineers, and analytics teams. • Collaborate with business leaders, product teams, and IT leadership. • Provide architectural guidance for data strategy and digital transformation initiatives. 1. Data Modeling & Integration • Design enterprise data models using tools such as: • ERwin Data Modeler • Informatica PowerCenter • Define standards for data integration, master data management (MDM), and APIs. Required Qualifications • Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field. • 17+ years of experience in data engineering, data architecture, or enterprise architecture. • Strong expertise in data warehousing, big data, and cloud data platforms. • Proven experience designing large-scale enterprise data platforms. • Expertise in SQL, Python, distributed data processing frameworks. Preferred Skills • Experience with Lakehouse architecture and modern analytics platforms. • Knowledge of AI/ML data pipelines and feature engineering platforms. • Experience with real-time streaming architectures. • Familiarity with data mesh architecture principles. Certifications (Preferred) • AWS Certified Data Analytics – Specialty • Microsoft Certified: Azure Data Engineer Associate • Google Professional Data Engineer Key Competencies • Strategic thinking and enterprise architecture design • Leadership and mentoring skills • Strong analytical and problem-solving abilities • Excellent stakeholder communication • Data governance and compliance expertise