Fractional Data Engineer (Consultant)

Department: G&A Location: Washington, DC Description The Bulwark isn’t just a business, it’s a mission. We're a fast-growing media company founded to provide analysis and reporting in defense of liberal democracy. Our podcasts, newsletters, and videos cut through the noise to deliver sharp, independent analysis. Inside The Bulwark, we live by a few simple rules: candor over spin, collaboration over ego, and a commitment to making each other better. We’re a nimble, fast-moving team that takes our work seriously—but not ourselves. We’re seeking a fractional Data Engineer (consultant) to help us build the data foundations that power our audience growth, subscriptions, and long-term sustainability. This is a part-time consulting engagement (initial ramp-up followed by ~5-10 hours/week) ideal for someone who enjoys high-impact projects, autonomy, and helping a scaling media company level up its analytics. About the Engagement The Bulwark is building the core infrastructure needed to better understand how audiences find, engage with, and subscribe to our work. We’re looking for a consultant who can design the foundational systems, definitions, and pipelines we need—and then provide ongoing support as we operationalize and learn from the data. This role is structured around clear deliverables and discrete project phases, not ongoing day-to-day operational ownership. You’ll work across Snowflake, Substack, and additional data sources to build a reliable analytics environment and surface the insights that matter most. Phase 1: Initial Build-Out (Project-Based)In the first 6–10 weeks, you will lead the design and implementation of our core data foundations. Data Architecture & Ingestion: • Audit existing data sources and ingestion pathways across Snowflake, Substack, web/app analytics, and other platforms. • Design a source-of-truth schema for subscriber, engagement, and revenue data. • Build or refine ingestion and transformation processes using Snowflake SQL (and adjacent tooling). Definitions & Metrics Framework: • Create clear, durable definitions for key business metrics (subscriber value, engagement, retention, attribution, cohort logic, etc.). • Develop an actionable metrics dictionary and documentation set to ensure consistency across teams. Analytic Foundations: • Build baseline retention, attribution, funnel, and cohort analyses to inform growth strategy. • Work with our Business Ops Manager to improve dashboards and reporting. Documentation: • Document data sources, logic, assumptions, and workflow diagrams to make systems transparent and maintainable. Phase 2: Ongoing Fractional Support (~5-10 hours/week)After the initial build-out, the consultant will remain engaged part-time to: • Maintain and refine existing pipelines as needed. • Run recurring analyses (e.g., monthly retention/cohort review, channel performance updates). • Provide ad-hoc exploratory analyses tied to audience growth or subscription trends. • Troubleshoot instrumentation or backend data flow questions. • Provide light mentorship to Growth/Business Ops on SQL, data literacy, and analytic approaches. This phase is flexible and task-based, focused on sustaining and optimizing the systems created in Phase 1—not standing up brand-new infrastructure from scratch each week. About You You bring: • 4+ years of hands-on experience in data engineering, analytics engineering, or analytics (subscription media or consumer product experience strongly preferred). • Strong SQL skills, ideally with Snowflake experience. • Experience stitching together disparate or imperfect datasets—and comfort navigating constraints on platforms like Substack. • Familiarity with analytics/visualization tools (Tableau, Looker, Geckoboard, Mode, Metabase, or similar). • Ability to work independently, communicate clearly, and produce high-quality work with limited oversight. • A problem-solver’s mindset and a bias toward building durable, lightweight systems rather than over-engineered ones. Bonus: • Experience designing subscriber attribution or cohort frameworks. • Experience building LTV or churn models. • Experience helping non-technical teams improve their data fluency. Instructions To apply, please submit your resume and a brief application. Short responses are welcome—we’re looking for clarity, not length.