About the role
<div class="content-intro"><p><img style="max-width: 100%;" src="https://66degrees.com/wp-content/uploads/2025/03/JobPosting-Cover.jpg" alt="" width="1400"></p> <h2>Overview of 66degrees</h2> <p>66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential.</p> <p>At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.</p></div><h2>Overview of Role</h2> <p>We are seeking an experienced Data Architect to design, develop, and maintain our google cloud data architecture. The ideal candidate will have a strong background in data architecture, data engineering, and cloud technologies, with experience in managing data across google cloud platforms.</p> <h2>Responsibilities</h2> <ul> <li>GCP Cloud Architecture: Design, implement, and manage robust, scalable, and cost-effective cloud-based data architectures on Google Cloud Platform (GCP), leveraging services like BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage, Cloud DataProc, Cloud Run, and Cloud Composer. Experience designing cloud architectures on Oracle Cloud is a plus.</li> <li>Data Modeling: Develop and maintain conceptual, logical, and physical data models to support various business needs.</li> <li>Big Data Processing: Design and implement solutions for processing large datasets using technologies such as Spark and Hadoop.</li> <li>Data Governance: Establish and enforce data governance policies, including data quality, security, compliance, and metadata management.</li> <li>Data Pipelines: Build and optimize data pipelines for efficient data ingestion, transformation, and loading.</li> <li>Performance Optimization: Monitor and tune data systems to ensure high performance and availability.</li> <li>Collaboration: Work closely with data engineers, data scientists, and other stakeholders to understand data requirements and provide architectural guidance.</li> <li>Innovat