Lead Data Architect

Data Architect

Job Summary :

We are looking for a seasoned and visionary Data Architect with over 14 years of experience to lead the design and implementation of enterprise-grade data architecture, governance frameworks, and scalable data platforms. This role requires deep expertise in modern data technologies, big data ecosystems, and cloud-native solutions. The ideal candidate will be a strategic leader who can bridge business needs with technical solutions, ensuring data integrity, quality, and accessibility across the organization.

Key Responsibility :

• Lead the design and implementation of Data Architecture, Data Quality frameworks, and Data Governance initiatives.
• Define data modeling standards and establish foundational best practices across data platforms.
• Champion and promote data quality principles by developing and institutionalizing enterprise-wide standards and methodologies.
• Build and oversee data governance policies, procedures, and frameworks to ensure data integrity, security, and compliance.
• Drive enterprise-wide adoption of self-service data platforms and enablement of organizational data literacy and utilization.
• Define and maintain critical data standards and metadata to facilitate the consistent understanding and use of data as a shared enterprise asset.
• Create reusable templates and establish coding standards for sourcing, collecting, and transforming both streaming and batch data.
• Design scalable data schemas, object models, and flow diagrams to effectively structure, process, and integrate data across systems.
• Provide architectural strategy, assessments, and roadmaps to guide enterprise data management practices.
• Offer hands-on expertise in architecting and managing Big Data platforms and Data Lake technologies (e.G., AWS S3, Hive), along with exposure to ML and Data Science tools.
• Implement and manage industry-standard tools and frameworks such as Databricks, Delta Lake, Apache Spark, Airflow, Hive Metastore, Redshift, Kafka, Kubernetes, Docker, and CI / CD pipelines.
• Translate complex big data and analytics requirements into high-performance, scalable data models and guide analytics engineers on implementing these models.
• Define reusable templates and processes for data modeling, data flow design, and system integration.
• Lead, mentor, and upskill data analytics teams by promoting best practices, modern technologies, and effective processes in data platform engineering.

Tech Skills :