Lead Data Engineer

Jobtailor; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor in New York seeks an experienced leader to own and scale a data platform end-to-end. You will drive dbt development, CI/CD, and Snowflake infrastructure while onboarding new data sources as the business grows.

You will partner with product, growth, finance, CX, and portfolio teams to model data sources, prioritize a demanding roadmap, and uphold data quality with contract-enforced schemas. Leadership and AI fluency are essential to guide the team and evolve the platform.

Qualifications

• A track record of leading engineers and teams.
• 8+ years in data engineering (or software with data focus) including team growth.
• Deep SQL and dbt expertise.
• Hands-on with Snowflake or comparable MPP warehouse.
• Experience scaling data platforms during growth.
• Strong architecture and code review skills.
• Stakeholder management and business mindset.
• AI fluency and ability to integrate AI into data processes.

Responsibilities

• Own the data platform end-to-end—from dbt projects to CI/CD and Snowflake infra.
• Design and onboard new data sources as the platform scales.
• Partner with product, growth, finance, CX, and portfolio teams to model sources.
• Run intake and prioritization across a high-demand roadmap.
• Protect data quality via dbt tests and contract-enforced schemas.
• Set technical direction for the warehouse and perform code reviews.
• Lead and grow the data team with 1:1s, feedback, and career development.
• Build the factory and infuse AI into team processes.

Skills

Data Leadership

SQL Expertise

dbt Proficiency

Snowflake Experience

AI Fluency

Team Leadership

Stakeholder Mgmt

Tools

Snowflake

Redshift

BigQuery

Job description

• Own the data platform end-to-end — the dbt project (staging → intermediates → marts), CI/CD, and the Snowflake infrastructure it runs on.
• Design and lead the onboarding of new data sources onto the platform as TTG scales.
• Partner with data consumers — product, growth, finance, CX, and incoming portfolio teams — to model new sources cleanly.
• Run intake and prioritization across a high-demand roadmap.
• Protect data quality systematically — dbt tests, contract-enforced schemas.
• Set technical direction for the warehouse and give code review that makes data engineers better.
• Lead and grow the team — 1:1s, feedback, and career development.
• Build the factory, not just the models: keep pushing AI into how the team works.

Requirements

• A track record of leading engineers.
• 8+ years in data engineering (or software engineering with a heavy data bent), including leading a team — formally or informally — and growing the engineers around you.
• Deep SQL and dbt expertise.
• Hands-on experience with Snowflake or a comparable MPP warehouse (Redshift, BigQuery).
• Experience scaling a data platform through growth.
• Full-stack data platform judgment.
• Strong architecture and code review.
• Stakeholder management.
• A product and business mindset.
• AI fluency.
• *You don't need to tick every box. If most of this sounds like you, we'd love to hear from you.*

Core Competencies

Demonstrates expertise in leading data engineering teams and managing data platforms, with a strong focus on SQL, dbt, and Snowflake. Capable of driving data quality, stakeholder management, and integrating AI into data processes.

Highest-signal resume keywords

• Data Engineering Leadership
• Deep SQL Expertise
• Dbt Proficiency
• Snowflake Experience
• AI Fluency

ATS Optimization Keywords

Hard Skills

• SQL
• Dbt
• Data Platform Scaling
• Architecture Design
• Code Review

Soft Skills

• Stakeholder Management
• Team Leadership
• Feedback and Career Development

Industry Keywords

• Data Quality
• CI/CD
• Data Modeling
• Data Warehouse
• Product Mindset

Tools & Technologies

• Snowflake
• Redshift
• BigQuery