Senior Data Architect, Data Warehouse & Analytics

CoreWeave is the AI Hyperscaler™, delivering a cloud platform of cutting edge services powering the next wave of AI. Our technology provides enterprises and leading AI labs with the most performant, efficient and resilient solutions for accelerated computing. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe. CoreWeave was ranked as one of the TIME100 most influential companies of 2024.

As the leader in the industry, we thrive in an environment where adaptability and resilience are key. Our culture offers career-defining opportunities for those who excel amid change and challenge. If you’re someone who thrives in a dynamic environment, enjoys solving complex problems, and is eager to make a significant impact, CoreWeave is the place for you. Join us, and be part of a team solving some of the most exciting challenges in the industry.  

CoreWeave powers the creation and delivery of the intelligence that drives innovation. 

What You’ll Do

The Data Warehouse & Analytics team builds foundational datasets and analytics services that enable BI and data science across CoreWeave’s cross-functional domains. We seek to democratize insights and foster a culture where data-driven decision-making thrives at every level.

We’re seeking a skilled Senior Data Architect to lead the development of foundational data models that empower our Business Intelligence Engineers, analysts, and data scientists to efficiently work with and gain insights from our enterprise data across capacity, infrastructure engineering, and supply chain. This role will own the creation and maintenance of star and snowflake schemas within our lakehouse environment and set the standards for dimensional modeling best practices. The architect will also create and optimize key datasets and metrics essential to tracking business health.

• Develop and maintain business transformation rules and data models, including star and snowflake schemas, to support analytical needs across the organization.
• Establish and enforce best practices for dimensional modeling in our Lakehouse.
• Architect and optimize data storage using analytical table/file formats (e.g., Iceberg, Parquet, Avro, ORC).
• Partner with BI, analytics, and data science teams to design datasets that accurately reflect business metrics.
• Tune and optimize data in MPP databases such as StarRocks, Snowflake, BigQuery, or Redshift.
• Collaborate on data workflows using Airflow, building and managing pipelines that power our analytical infrastructure.
• Ensure efficient processing of large datasets through distributed computing frameworks like Spark or Flink.
• Develop BI / GenBI dashboards that answer key questions of stakeholders using tools like Grafana and Tableau

Investing in our people is one of our top priorities, and we value candidates who can bring their diversified experiences to our teams. Here are some qualities we’ve found compatible with our team. We'd love to talk about whether this aligns with your experience and Interests and what you’re excited to work on next.

Who You Are

• 10+ years of experience working in a Cloud hyperscaler environment with a solid understanding of supply chain, capacity, and infrastructure engineering domains.
• Ability to thrive in a fast-paced, complex, work environment tackling hard problems.
• Hands-on experience applying Kimball Dimensional Data Modeling principles to large datasets.
• Expertise in working with analytical table/file formats, including Iceberg, Parquet, Avro, and ORC.
• Proven experience optimizing MPP databases (StarRocks, Snowflake, BigQuery, Redshift).
• 5+ years of programming experience in Python or Scala.
• Experience transforming raw source data into high-quality data warehouse dimensions and facts using a transformation tool such as DBT
• Advanced SQL skills, with a strong ability to write, optimize, and debug complex queries.
• Hands-on experience with Airflow for batch orchestration distributed computing frameworks like Spark or Flink.
• Preferred: Professional Cloud Architect certification

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $175,000-$205,000. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.