Senior Data Architect

We are seeking an experienced Data Architect to design and build the foundation of our data and analytics ecosystem. This role goes beyond developing pipelines and optimizing performance-it is about creating a scalable data platform that empowers teams to make better decisions, uncover insights, and drive innovation.

As a key member of the organization, you will lead the development of our enterprise data warehouse and data infrastructure, partnering closely with engineering and product teams to ensure reliable, efficient, and scalable data ingestion and processing. You will also play a critical role in establishing data governance standards, architecture best practices, and the long-term strategy for analytics, reporting, and AI-driven initiatives.

If you enjoy building systems from the ground up and shaping the future of data within a growing organization, we'd love to connect.

Responsibilities

• Design, build, and maintain a scalable, secure, and high-performing data warehouse.
• Develop and optimize ETL/ELT pipelines to process structured and semi-structured data from multiple sources.
• Partner with software engineering and product teams to onboard, structure, and leverage new data assets.
• Create and maintain data models, schemas, and architectures that support analytics, reporting, and future AI/ML initiatives.
• Establish and enforce best practices for data governance, quality, security, and compliance.
• Implement monitoring, alerting, and observability solutions to ensure reliable and accurate data pipelines.
• Document data architecture, workflows, and technical decisions to support knowledge sharing and operational excellence.
• Drive continuous improvement of the organization's data infrastructure and processes.

• Proven experience designing, implementing, and maintaining data warehouses from the ground up.
• Hands-on expertise with AWS data technologies (Redshift, S3, Glue, Athena) and/or Google BigQuery. Experience with both platforms is highly preferred.
• Advanced SQL skills and strong expertise in analytical data modeling.
• Demonstrated experience building and supporting robust ETL/ELT pipelines for high-volume, real-time, or near-real-time data environments.
• Strong proficiency with Python or similar scripting languages for data processing and automation.
• Deep understanding of data privacy, security, governance, and compliance requirements, including GDPR and CCPA.
• Excellent communication and collaboration skills, with the ability to work cross-functionally across technical and business teams.
• Ability and willingness to work on-site in Chicago, IL., * Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent practical experience).
• Experience working in startup or high-growth environments.
• Familiarity with data visualization and BI platforms such as Looker, Tableau, or Power BI.
• Knowledge of event-driven architectures and streaming technologies such as Kafka, Kinesis, or Google Pub/Sub.
• Passion for mentoring teammates and contributing to a strong data culture.