Data Platform Engineer
Summary
The Data Platform Engineer will design and build production-grade data pipelines and systems to support analytics and AI initiatives. The role involves managing core platforms like Snowflake, dbt, and Dagster while driving data reliability and self-service tooling for the organization.
Responsibilities
- Design and build the data systems that power analytics, AI, and business intelligence across Owner
- Replace one-off custom scripts with reproducible, production-grade pipelines
- Own and evolve core platforms including Snowflake, dbt, Dagster, and ingestion/reverse ETL layers
- Improve data reliability, consistency, and compliance
- Move the team to self-service tooling for analysts and partners
- Identify and drive cost and performance optimizations
- Drive technical decisions and best practices for ingestion, transformation, orchestration, and storage
- Provide thoughtful code reviews and technical guidance to peers
Requirements
- 5+ years of data engineering or analytics engineering experience
- Strong SQL and Python fluency
- Hands-on production experience with Snowflake
- Deep ETL/ELT fundamentals, including dbt and a modern orchestrator such as Dagster or Airflow
- Proven track record of impact-driven problem-solving in fast-paced environments
- Excellent technical communication skills
- Comfort building from zero
- A sense of ownership, curiosity, and commitment to continuous learning
Preferred Qualifications
- Experience building a semantic layer or data infrastructure for AI/ML and LLM retrieval
- Experience with reverse ETL or personalization platforms
- Databricks experience
- Experience with data governance, access control, and cost optimization
- Experience mentoring engineers
- Genuine interest in the product and its customers