Overview
Principal Data Engineer responsible for technical direction across a significant product domain, building and maintaining data pipelines that support reporting and AI-driven products.
What you'll do
- Drive technical direction for a significant product domain or platform capability.
- Design and maintain data pipelines that feed AI systems such as RAG ingestion, embeddings, and vector stores.
- Use AI-assisted engineering tools and help other engineers adopt them.
- Lead architectural debt remediation and manage ongoing technical debt.
- Partner with product and engineering leadership on multi-quarter roadmap feasibility and provide technical guidance.
- Elevate engineering craft through RFCs, mentorship, knowledge sharing, and training programs.
- Represent technical capabilities externally via conferences, open-source contributions, and industry engagement.
What you'll need
- 10+ years of experience in software engineering with a focus on technical leadership and architecture.
- Deep understanding of data engineering principles including data modeling, data warehousing, reporting, and data governance.
- Strong expertise in SQL, PostgreSQL, ETL/ELT pipelines, BI tools, and analytics platforms.
- Comfort using AI coding assistants such as Claude Code, Copilot, and Cursor.
- Practical experience with AI/LLM-adjacent data work such as RAG ingestion pipelines, embedding generation, vector stores, and AI data governance/quality.
- 2+ years of experience on Ruby on Rails, React, and modern cloud platforms such as AWS.
- Experience leading cross-functional initiatives with product, engineering, analytics, and business teams.
Nice to have
- Experience with a semantic or metrics layer (e.g., dbt Semantic Layer, headless BI).
- Experience with BI, reporting, dashboards, and customer-facing analytics.
- Understanding of CI/CD, Git-based workflows, and infrastructure-as-code.
Details
- Stack tools mentioned include Fivetran, Airbyte, dbt, Snowflake, GitHub, and Terraform.
Negotiable
Posted yesterday
10+ Years
