• Contribute to the Snowflake migration: Work with the broader data team to deprecate our legacy Redshift and Apache Hop infrastructure by completing the migration to Snowflake and dbt Cloud • Build production-grade dbt pipelines: Develop and maintain SQL transformations in dbt that power analytics for business stakeholders across the organization • Establish data architecture: Refine and maintain our medallion architecture (bronze, silver, and gold layers) to create clear separation of concerns and a single source of truth • Collaborate with the data team: Partner with our AWS Engineer, Analytics Engineer, and Business Analyst in a sprint-based workflow with code reviews and regular standups • Maintain dbt transformations (60-70% of role): Own approximately 15-20 core models and summary views that drive business reporting, ensuring they're performant, well-documented, and easy to maintain • Build new data pipelines: Ingest data from APIs and new sources as business needs evolve • Enable reverse ETL: Develop and manage batch processes to send transformed data to downstream services like HubSpot using tools like Hightouch • Monitor data quality: Implement testing and alerting to catch issues before they impact stakeholders • Contribute to technical standards: Help establish and maintain best practices for code quality, documentation, and data modeling

• responsible for the end-to-end design, delivery, governance, and modernization of Orgain’s enterprise integration ecosystem and data architecture • focuses on data engineering, metadata and lineage, data governance, master data management, and scalable enterprise data platform capabilities • define, build, and govern enterprise application portfolio integrations (MS Fabric, APIs, middleware, database replication, secure file interchange) • own the enterprise data platform architecture (lake, warehouse, semantic/subject layers) • lead enterprise-wide IT programs, including digital supply chain and data platform initiatives • implement metadata, lineage, catalog, and data governance frameworks to ensure trusted, discoverable, and compliant data • establish master/reference data management foundations with clear stewardship, quality controls, and ownership • direct partner and vendor delivery; set standards for quality, documentation, technical design, and knowledge transfer • collaborate with the Business Intelligence team to ensure data models are ready for consumption while maintaining strict below-the-line boundaries • lead complex multi-workstream technology delivery initiatives, coordinating across IT, Finance, eCommerce, Supply Chain, and external partners • maintain integration service catalog and blueprint; enforce secure, durable, and governed integration practices • design durable standard models and schemas optimized for analytics, operational reporting, and cross-application interoperability • implement data quality management processes including validation, profiling, reconciliation, and automated monitoring • define versioning and release/change management standards for data and integration components • set individual goals for improving and expanding on everyday job functions, as well as on the greater social and environmental aspects of your work • help enhance Orgain’s social and environmental impact • coach/lead and provide interpersonal relationship development for all direct reports.

• Architect, design, and maintain robust, scalable data pipelines and infrastructures for geospatial and big data applications maintaining a focus on performance and the ultimate end-user product experience. • Lead the development and optimization of ETL processes for ingesting, cleaning, transforming, and storing large volumes of geospatial and tabular data. • Design, build, and interact with API-driven, service-to-service web services (using FastAPI, Litestar, Flask, etc.) to enable integration across a suite of products. • Collaborate with backend and platform engineers to ensure secure, reliable, and scalable service-to-service communication. • Translate complex analytics and business questions into actionable, production-grade data solutions. • Collaborate closely with data scientists, analysts, and business stakeholders to deliver high-impact data products. • Drive the adoption and optimization of cloud-based data solutions (e.g., GCP, AWS, Azure). • Ensure data quality, integrity, and security across all stages of the data lifecycle. • Mentor and provide technical guidance to junior data engineers and team members. • Communicate technical details and insights clearly to both technical and non-technical audiences, including leadership. • Proactively recommend and implement improvements to existing data infrastructure and software programs. • Stay current with industry trends and emerging technologies in geospatial data engineering.

• Build and support high performance data solutions • Monitoring and responding to our growing network of tools • Facing and overcoming complex technical challenges