[Hiring] Senior Data Engineer @Eve

Role Description

Eve is doubling revenue quarter over quarter, and the platform is being built to keep pace. A medallion architecture is in place on a Terraform-managed Snowflake footprint. Most of what goes on top is still ahead:

• Ingestion and orchestration built for the volume coming
• Reliability practice
• Access and governance model
• Standards every contributor works inside

The data spans product usage, case and firm data, and every go-to-market system Eve runs on. Analytics engineers and business analysts build models and reporting on top of it, AI agents query it directly, and leadership makes calls on it weekly. When a pipeline fails quietly, all three inherit the mistake.

You'll own the pipelines carrying all of that, end to end, from an ambiguous ask through to production:

• Moving nightly rebuilds onto incremental patterns
• Deciding how a new source gets ingested and what happens when it changes shape
• Building the alerting that catches a broken model before anyone downstream does
• Being the one who picks it up when it breaks

You'll have real say in how the platform gets built. You'll work on our central team and report to the Head of Data Engineering, who reports directly to the CEO. Data is a first-class function at Eve and the fuel to drive our future growth.

Qualifications

• 5+ years in data engineering, owning production systems other people depended on
• Strong Python and SQL, with production experience across ingestion (Fivetran or similar), orchestration (dbt platform, GitHub Actions, or Airflow), and cloud infrastructure
• Solid Snowflake: access control, warehouse sizing, query performance, and cost management
• Practical dbt: incremental models, testing, macros, and a git-based workflow with CI
• Comfort in a Terraform-managed environment
• You've built reliability practice where none existed: alerting, freshness SLAs, incident response, schema change detection
• Proficiency with AI-assisted development such as Claude Code
• Able to tell a stakeholder what broke, what it affected, and when it'll be fixed, without the jargon
• Comfort building where the playbook doesn't exist yet

Requirements

• Experience in a regulated or high-sensitivity data environment (legal, healthcare, financial services)
• Experience with streaming or near-real-time ingestion, and knowing when it isn't worth it
• Exposure to Iceberg, Parquet, or unstructured data at scale
• B2B SaaS, especially selling to small and mid-sized businesses or professional services firms

Benefits

• 💰 Competitive Salary & Equity
• 💹 401(k) Program with Employer Matching
• ⚕️ Health, Dental, Vision and Life Insurance
• 🩼 Short Term and Long Term Disability
• 🚗 Commuter Benefits
• 🧑‍💻 Autonomous Work Environment
• 🖥️ Workplace Setup Reimbursement
• 🏠 Telecomm Stipend
• 🏝 Flexible Time Off (FTO) + Holidays
• 🚀 Quarterly Team Gatherings
• 🥪 In office Perks