Description:
We’re looking for a Lead Data Engineer to spearhead the design, implementation, and iteration of a world-class, modern data infrastructure that powers analytics, data science, and ML/AI systems. You will be in the driver’s seat for a new function on the Engineering team and will help chart its future.
This role is highly strategic, cross-functional, and hands-on. If you’re passionate about building 0→1 data platforms collaboratively and have experience scaling them at a rapidly growing startup, this role is for you.
What you will do
- Define and execute the strategic roadmap for data infrastructure and analytics capabilities across the organization.
- Partner closely with Data Science, Operations Analytics, Engineering, and Product on the design and implementation of scalable data pipelines, models, and solutions.
- Drive the development of foundational data products and tools to power self-service analytics.
- Actively contribute to and influence engineering processes, culture, practices, and systems.
- Serve as a technical thought leader on data engineering best practices.
About you
- Strong technical foundation with the modern data engineering stack (dbt, PySpark, Fivetran, Snowflake, Lakehouse, CDPs, ETL tools, etc.).
- Advanced knowledge of SQL and Python.
- Deep expertise in data pipelines, distributed systems, and analytics infrastructure.
- Hands-on experience with data warehousing technologies, data lake architecture, and ETL pipelines/tools.
- Deep understanding of BI tooling infrastructure and semantic layer design (e.g., Looker, Tableau, Metabase, Mode).
- Experience and interest in leading major architecture initiatives from the ground up.
- Believer in applying best-in-class software engineering practices to data systems.
- Interest in coaching/mentoring junior engineers.