Senior Engineer, Data Engineering

National Debt Relief (NDR) is seeking a Senior Data Engineer to help shape the architecture, reliability, and evolution of the data platform that supports analytics and decision-making across the business. Reporting to the Senior Data Engineering Manager, this role will own one or more data domains across our Snowflake-based platform, spanning ingestion, orchestration, transformation, and analytics-ready data models.

We are an AI-first engineering team, and AI coding agents are a core part of how we develop and maintain our platform. The ideal candidate brings exceptional SQL and data modeling skills, deep expertise in one or two areas of the modern data stack, and strong range across the rest. Success in this role means turning ambiguous problems into durable solutions, owning production outcomes for critical data, establishing patterns others can build on, and raising the technical bar through design, review, and mentorship.

Essential Duties/Responsibilities

• Own the architecture and reliability of one or more data domains end to end, establishing patterns and conventions other engineers can build on.
• Take ambiguous, cross-cutting problems from definition through verified delivery, making and defending tradeoffs tied to business outcomes, reliability, and cost.
• Identify architectural, reliability, and maintainability improvements across the platform and translate them into well-scoped initiatives, influencing priorities and technical direction.
• Develop and maintain Python-based ingestion pipelines when custom pipelines are required, integrating data from APIs and third-party systems.
• Design and build data pipelines and workflows using dbt, Python, Dagster, and Snowflake, documenting significant designs and weighing failure modes, scalability, cost, and maintainability.
• Use AI coding agents as a core part of daily work while creating reusable workflows, verification practices, and guardrails for the broader team.
• Build systemic safeguards for data quality and trust through testing, data contracts, monitoring, reconciliation, and alerting that prevent recurring issues.
• Own domain reliability, including SLAs, alerting, runbooks, morning load failures (Eastern Time working hours), on-call rotation, complex incident response, and post-incident review.
• Manage Snowflake infrastructure and access controls for sensitive data through infrastructure-as-code, following security, governance, and privacy standards.
• Optimize Snowflake performance and compute costs through efficient query design, warehouse tuning, architecture decisions, and resource monitoring.
• Grow other engineers through design and code review, pairing, mentorship, documentation, and clear technical guidance.

Education/Experience

• 7 years of experience in data engineering, analytics engineering, or data warehouse development, including ownership of production data systems in a cloud environment.
• Bachelor's degree in a relevant technical field, or equivalent practical experience.
• Experience using Python to build or maintain integrations with APIs and third-party data sources.
• Experience implementing CI/CD workflows, version control, automated testing, and observability for production data pipelines.

Required Skills/Abilities

• Expert SQL and data modeling across a domain, including grain, keys, conformed dimensions, incremental strategies, layered architecture, and semantic implications.
• Strong working proficiency across dbt, Dagster, and Snowflake, plus proficiency in Python and infrastructure-as-code, with expert-level depth in one or two areas of the stack.
• Advanced proficiency using AI coding agents, including recognizing likely failure modes, providing effective context and constraints, critically verifying generated work, and creating reusable workflows or guardrails.
• Strong architecture and systems thinking across dependencies, failure modes, scalability, security, maintainability, and cost.
• Systematic root-cause analysis across multiple layers of the platform, identifying subtle or systemic problems and driving durable corrective action.
• High autonomy: able to operate from desired outcomes rather than prescribed approaches, make progress with incomplete information, and drive ambiguous work to closure.
• Clear communication of complex technical topics to engineers, analysts, business stakeholders, and leadership, with a track record of mentoring other engineers.
• Strong business acumen and prioritization judgment, connecting technical decisions to…