• Design, build, and maintain scalable data pipelines using BigQuery and dbt • Architect and optimize warehouse-first data models to support analytics, marketing, and operational reporting • Develop and maintain Looker dashboards and semantic layers • Integrate and transform data from Shopify, Klaviyo, Loop (subscriptions/returns) and 3PL systems (e.g., ShipHero, ShipBob, etc.) • Build automated workflows for data ingestion, validation, and monitoring • Implement best practices for data quality, governance, and documentation • Leverage AI tools (LLMs, automation frameworks) to: Accelerate data transformation workflows Refactor and optimize SQL/dbt models Automate anomaly detection and QA processes • Collaborate with analytics, product, and marketing teams to translate business requirements into scalable data solutions • Troubleshoot data discrepancies and provide root-cause analysis • Recommend architectural improvements to improve performance, reliability, and scalability

• Development of various services in Python: integration with marketing partners, obtaining data from various sources • Creation and support of processes on Airflow • Development/refinement of reports on SSRS / SuperSet dashboards • Creation/support of SQL DWH, creation/support of stored procedures • Supporting the migration of marketing data pipelines and DWH components from MS SQL to Google Cloud Platform (including BigQuery), contributing to architecture decisions and best practices.

Role Description Cedar is at a pivotal moment in its technical evolution. We are evolving towards a brand-new, enterprise data platform and model, architected specifically to power the future of Cedar’s product offerings. As the Principal Data Architect, you will be the senior technical authority leading this transition, ensuring our new data foundation is clean, scalable, and cleanly separated from legacy debt. This is a hands-on technical leadership role for an engineer who loves building production systems at scale and views AI as a massive accelerator for both personal and team productivity. What You’ll Do - Architect the Future-State Data Model & Storage: Lead the design and execution of a new, high-scale data model and storage architecture that lives outside our legacy monolith. - Ensure Metrics Reliability: Own the accuracy and reliability of Cedar’s core business metrics including collection rate, days in AR, and invoice balance tracking. - Power Intelligent Agents: Build the real-time data foundations that power Cedar’s AI-driven products. - Design for the Future: Design data models for new product lines that expand Cedar’s presence across the full revenue cycle. - Build Production Code: Write, ship, and maintain high-quality production code alongside our team of Data Engineers. - Guide and Mentor Engineers: Act as the technical role model for a team of Data Engineers. - Collaborate: Drive technical alignment across data engineering, platform, and product teams. - Steward Data Integrity: Define and enforce standards for Cedar's enterprise Data Dictionary and metadata strategy. Qualifications - 10+ years of experience in data engineering and backend systems at scale. - Experience leading large technical projects with a high accountability mentality. - Deep, hands-on proficiency with a wide range of data and engineering technologies and patterns. - Experience building "source of truth" systems and a passion for data accuracy. - Experience building data APIs, context systems, or feature stores that power downstream ML/AI applications. - Ability to spot over-engineering and under-engineering with equal confidence. - Clear communication skills to translate complex technical risks and trade-offs into business-relevant terms. - Avid learner and adopter of AI engineering tools. - Demonstrable understanding of healthcare concepts, including revenue cycle management (RCM), billing, and insurance adjudication (highly preferred). Requirements - Experience with technologies such as Snowflake, dbt, Liquibase, Fivetran, Airflow, OpenMetadata, Kafka, SQL, Python, and real-time data processing. - Experience with building production-grade ELT/ETL pipelines and managing complex data transformations in cloud-first environments. - Experience with data validation and reconciliation, comparing pipeline output against source systems. Benefits - Salary/Hourly Rate Range: $246,500 - $311,750. - This role is equity eligible. - This role offers a competitive benefits and wellness package. - Unlimited PTO for vacation, sick, and mental health days. - 16 weeks paid parental leave with health benefits for all parents. - Diversity initiatives that encourage Cedarians to bring their whole selves to work. - Competitive pay, equity (for qualifying roles), and health benefits. - Cedar matches 100% of your 401(k) contributions, up to 3% of your annual compensation. - Access to hands-on mentorship, employee and management coaching, and a team discretionary budget for learning and development resources.

• Establish and uphold the goals and expectations that support the fulfillment of cultural and business objectives. • Operate with a team-first mindset, committed to ensuring the overall success of the team and organization. • In collaboration with the Part D business team and BI engineers, lead data engineering solutions (design, data movement, orchestration, optimization) for prioritized business requests impacting organizational and enterprise initiatives. • In Databricks: design, build, maintain, and support the data analytics platform, ensuring the platform is optimized for performance and the right tools are being used for the right jobs. • Work collaboratively with teammates to optimally apply data warehouse, cloud, and BI architecture, normalization, and data visualization techniques to deliver solutions. • Create and impact data scale solutions at the QCSA/Enterprise level to meet business needs.