Chief Enterprise Data Strategist

We are seeking a talented data architect to design, develop and govern our enterprise data platforms. The ideal candidate will be collaborative, organized, think out-of-the-box, and be ready to pursue new opportunities.

• Data Architecture: Design scalable and robust data architectures for data warehousing and enterprise data platforms.
• Data Pipelines: Develop and optimize data pipelines and ETL/ELT/CDC workflows using tools such as Fivetran and Cloud Composer.
• Collaboration: Collaborate with data scientists, product managers, and business stakeholders to define data requirements and create logical and physical data models.
• Database Administration: Manage and administer various database systems including BigQuery, SAP HANA, and PostgreSQL.
• Data Quality: Ensure data quality, integrity and security across all data platforms and pipelines.
• Ai/Ml Integration: Work with our AI/ML teams to design data serving layers and feature stores that support Vertex AI workloads.
• Reporting Frameworks: Design and develop reporting frameworks and data marts to support business intelligence needs.
• Data Integration: Integrate data platforms with various enterprise systems (CRMs, ERPs) and third-party APIs.
• Data Governance: Define and implement data governance, master data management, and data cataloging strategies.
• Data Lifecycle: Contribute to the full data lifecycle: requirements gathering, architecture, data modeling, development, testing, and deployment.
• Troubleshooting: Troubleshoot and resolve data platform issues to ensure high availability and optimal performance.
• Documentation: Document technical designs, data lineage, and architecture for cross-functional reference.

Required Skills And Qualifications:

• Bachelor's Or Master's Degree: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
• Backend Language Proficiency: Proficiency in one or more backend languages/frameworks, with a strong preference for Python or Go.
• Restful API Experience: Experience with building RESTful APIs and designing microservices for data delivery.
• Data Modeling Fundamentals: Solid grasp of data modeling fundamentals, including Kimball and Inmon methodologies.
• Sql And Nosql Databases: Proficiency in writing complex SQL queries and experience with SQL and NoSQL databases.
• Data Warehousing Concepts: Familiarity with data warehousing concepts and best practices, including CDC.
• Version-Control Habits: Strong version-control habits (Git) and experience with CI/CD pipelines.
• Problem-Solving Skills: Excellent problem-solving, communication, and collaboration skills.
• Continuous Learning: Passion for continuous learning and adapting to emerging data technologies.

Preferred Qualifications:

• Hands-On Experience: Hands-on experience designing and deploying production-grade data warehouses.
• Gcp Experience: Deep experience with Google Cloud Platform (GCP): BigQuery for large-scale analytical workloads, Cloud Composer for orchestrating complex data pipelines, and Vertex AI for AI/ML model serving and feature stores.
• Cloud Providers: Experience with other cloud providers (AWS, Azure) and their data services.
• Data Governance Frameworks: Working knowledge of data governance frameworks, master data management, and data cataloging tools.
• Data Ingestion Tools: Experience with data ingestion tools like Fivetran.
• Business Intelligence Expertise: Business-intelligence expertise in building dashboards and reports with Power BI or Tableau.
• Familiarity With Other Data Technologies: Familiarity with other data technologies such as SAP HANA.
• Mlops Concepts: Understanding of MLOps concepts and their application to data pipelines.
• Contributions To Open-Source Projects: Contributions to open-source data projects or technical blogging/presentation.