Salary: $23/hour Location: Remote or Washington, D.C. Want to break into email? Get your start with us! Middle Seat is a consulting agency that works with some of the biggest names in progressive politics. We work with campaigns, nonprofits, and advocacy organizations on the front lines of racial justice, climate action, immigration rights, intersectional feminism, and economic justice.  We’re looking for a creative self-starter to support our Email team as a paid intern for SPRING 2026 (March 2026 - May 2026). What does the role involve? As an email intern at Middle Seat, you’ll work with our email team to write emails, you’ll use CRM platforms to code and produce emails, you’ll pull performance metrics and help assemble email reports, you’ll help analyze email performance, and you’ll also handle some email-related administrative tasks. This role is available either in person at our Washington, D.C office or remotely. This role is not part of the bargaining unit.

Salary: $23/hour Location: Remote or Washington, D.C. Email acquisition, direct donate, and persuasion. Want to break into digital? Get your start with us. Middle Seat is a full-service firm for progressive causes and candidates. We work with campaigns, nonprofits, advocacy organizations and causes on the front lines of racial justice, climate action, privacy and tech policy, immigration rights, and economic justice.  We’re looking for a creative self-starter to join our team as a paid digital advertising intern for SPRING 2026 (March 2026 - May 2026). What does the role involve? As an advertising intern at Middle Seat, you’ll work with the advertising team by trafficking ads, writing ad copy and petitions, pulling together reports, analyzing ads performance, handling some administrative tasks, and other responsibilities as requested. This role is available either in person at our Washington, D.C office or remotely. This role is not part of the bargaining unit.

• Transform and build robust solutions for transferring data from first and third-party applications to and from our data warehouse • Envision and design toward industry patterns on data exchange with our enterprise clients through a mix of traditional push delivery, cloud, and event-driven (eg: API, grpc) data sharing methods. • Support implementation and data integration as new partners roll onto the Bestow platform, and recommend improvements on configurability of platform. • Making decisions as a team. The things you build will be maintained and improved upon by others; there is a shared responsibility to make defensible design considerations and high collaboration. • Champion test-first design principles, proactively writing tests before code to maintain high coverage and pipeline reliability. • Develop hardened and repeatable (CI/CD) data models and pipelines to enable reporting, modeling and machine learning. • Ensure data quality through automated monitoring and alerting, and occasionally serving within an on-call rotation. • Leverage Google Cloud (GCP) tools (eg: Cloud Run, Cloud Functions, Vertex AI, App Engine, Cloud Storage, IAM, etc.) and services (eg: Astronomer - Apache Airflow) to bring data workloads to production. • Drive and support MLOps to improve Data Science monitoring and governance • Enable and support Generative AI (eg: LLM) pipelines, allowing internal teams to quickly prototype. Support the architecture and rollout of GenAI products and features into the marketplace. • Collaborate with product, engineering, stakeholders and data teams to deliver informed solutions to platform and client needs

• Assess legacy data and reporting workloads to identify where automation replaces manual effort. • Lead the migration of Informatica-based data workloads to Databricks, ensuring performance, reliability, and data integrity. • Design and execute an automation-first modernization strategy for data pipelines, reporting systems, and analytics platforms. • Apply tool-assisted and AI-assisted techniques to accelerate modernization while maintaining compliance and control. • Build repeatable frameworks and patterns for: Data ingestion, transformation, and orchestration; Reporting and analytics modernization; Data validation, reconciliation, and quality controls. • Establish governance to ensure modernization efforts are consistent, auditable, and scalable. • Partner with distributed data teams to deploy and scale modernization patterns across environments. • Provide hands-on technical leadership while remaining engaged in execution.