Data Architect

You will be part of the Cisco IT Data team, where technology, innovation, and collaboration drive real business value.

As a Data Architect, you will be the senior technical authority responsible for defining the architecture, standards, and strategic direction of Cisco's enterprise data platforms.

Key Responsibilities

• Define and own the enterprise data architecture vision, standards, and multi-year roadmap across ingestion, storage, transformation, discovery, and governance.
• Design scalable, secure, and highly available data architectures,including data lakes, lakehouses, data warehouses, and real-time streaming systems,leveraging modern cloud-native technologies.
• Define and lead target-state architecture and migration strategies that modernize legacy data infrastructure onto cloud-native platforms (e.g., GCP, Snowflake) to improve scalability and reduce operational cost.
• Establish architectural standards, reference patterns, and best practices for data modeling, integration, metadata management, and platform security across teams.
• Establish enterprise data modeling standards and governance/lineage frameworks that improve data quality, discoverability, and compliance across multiple business domains.
• Design API- and event-driven integration architectures that enable real-time data access across the enterprise, improving data delivery speed and reliability.
• Partner closely with data engineers, analytics teams, platform engineers, and business leaders to translate strategic priorities into robust, well-governed data solutions.
• Lead architecture decisions for platform modernization, evaluating and selecting technologies (e.g., Snowflake, BigQuery, Airflow, DBT, Informatica, Kubernetes) to optimize efficiency, cost, and scale.
• Define data governance, lineage, quality, and compliance frameworks, ensuring they are embedded across platform design and operations.
• Provide architectural oversight and design reviews, ensuring solutions meet reliability, scalability, performance, and security requirements.
• Champion conceptual, logical, and physical data modeling practices that support both operational and analytical workloads.
• Mentor engineers and architects, fostering a culture of technical excellence, sound design thinking, and knowledge sharing.
• Act as a key technical advisor to leadership, influencing architecture decisions, technology investments, and strategic direction across the data organization.

Minimum Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 13+ years of professional experience in data architecture, data engineering, or large-scale data platform design.
• Deep expertise designing enterprise data architectures,data lakes, lakehouses, and data warehouses,at scale.
• Strong proficiency with cloud platforms (AWS, GCP, or Snowflake) and modern, cloud-native data architectures.
• Expert-level data modeling skills (conceptual, logical, and physical) across relational, dimensional, and NoSQL paradigms.
• Proven experience defining data integration, ingestion, and API/microservices patterns for enterprise-scale systems.
• Strong knowledge of data pipeline orchestration tools (Airflow, DBT, Informatica) and cloud-native storage (Snowflake, BigQuery).
• Hands-on understanding of CI/CD, containerization (Docker, Kubernetes), and infrastructure as code (Terraform, CloudFormation).
• Solid programming or scripting skills (Python, SQL, Java, or similar) to support architecture validation and prototyping.
• Demonstrated success leading large, complex architecture initiatives and influencing across teams in Agile/Scrum environments.

Preferred Qualifications

• Experience designing real-time/streaming data architectures (Kafka, Pub/Sub) and large-scale ETL/ELT processes.
• Deep knowledge of data governance, security, lineage, and compliance frameworks.
• Experience architecting platforms to support AI/ML and advanced analytics workloads.
• Proven ability to optimize cost, performance, and scalability in cloud-based data environments at scale.
• Relevant architecture certifications (e.g., cloud architect, data architecture).
• Exceptional communication, influencing, stakeholder management, and mentorship abilities at the organizational level.