Director, Data Engineering (Data & AI Platform)

Location: Arlington, VA; remote candidates may be considered only if residing in a state where hirify.global or one of its subsidiaries has an established physical presence.

Salary: $157,100–$252,000 base salary annually, plus eligibility for up to 15% annual incentive compensation.

Company

hirify.global provides small business financing as a direct lender and marketplace connecting businesses with lending partners.

What you will do

• Own the engineering and solution architecture of a Snowflake-centered enterprise data platform, including data modeling, ingestion, transformation, orchestration, environments, and release controls.
• Define engineering standards for repositories, branching, CI/CD, testing, data quality, documentation, performance, cost management, and architectural governance.
• Lead the development of governed business data products from source onboarding through ELT pipelines, serving structures, validation, and production release.
• Direct the migration and decommissioning of legacy analytics workflows while improving platform security, reliability, observability, recovery, and operational readiness.
• Build data foundations for AI/ML, including feature-ready data, ML pipeline integration, and data flows for GenAI and agentic workloads.
• Lead internal engineers, partner delivery pods, and offshore teams while partnering with program, governance, architecture, and business stakeholders.

Requirements

• 10+ years of data engineering experience and 5+ years leading enterprise data platform builds or modernizations.
• Deep hands-on Snowflake expertise, including warehouse design, performance and cost optimization, security, access controls, data sharing, and production administration.
• Hands-on dbt mastery across project architecture, layered modeling, testing, documentation, macros, packages, CI/CD, and multi-environment delivery.
• Expert SQL skills with solid Python, Git-based workflows, CI/CD, automated testing, infrastructure-as-code awareness, and modern orchestration, ingestion, CDC, streaming, catalog, lineage, and semantic-layer experience.
• Experience designing enterprise-scale data architectures, leading distributed onshore/offshore teams, and delivering against validation and acceptance criteria.
• Understanding of ML and GenAI platform requirements, including feature pipelines, training and inference data flows, retrieval foundations, and monitoring.

Nice to have

• Financial services, lending, banking, fintech, data governance, model risk, or audit experience.
• Databricks, SnowPro, dbt, AWS, or Azure certifications.
• Consulting or professional services delivery experience, data product operating models, data mesh, data contracts, certified metrics, or FinOps.

Culture & Benefits

• Fast-paced environment with an emphasis on self-direction, accountability, transparency, fairness, and integrity.
• Medical, dental, vision, disability, life, and supplemental insurance options.
• Paid maternity and parental leave, paid time off, and sick time.
• 401(k) plan with a 25% match on contributions, up to 6% of annual salary.
• Tuition reimbursement of up to $5,000 annually, conference and career development opportunities, and travel reimbursement for work-related travel.
• Commuter, lifestyle, wellness, travel, and family-oriented discount programs.