The Role
Design and build enterprise-scale Snowflake environments, develop and optimize data pipelines with Python, dbt, and Airflow, lead client technical strategy, implement Snowflake security/compliance, and mentor junior engineers while collaborating with Snowflake, AWS, and Anthropic partners.
Summary Generated by Built In
The Mission
Key Responsibilities
Essential Requirements
Why Join?
Working on problems worth solving. At Applied Curiosity, we build responsible and informed decision cultures at our clients. Everyone lives and breathes data an AI, so you’ll be surrounded by an inquisitive, technical, and outcome focused group. If this is your jam, we are your people. We are a Snowflake, AWS, and Anthropic partner, and we’re looking for data engineering folks that love diagramming the big picture and then executing spectacularly so that the vision comes to life.
Key Responsibilities
- Architect & Build: Design enterprise-scale Snowflake environments (multi-account, cost-optimized).
- Develop Pipelines: Build and optimize data flows using Python, dbt, and Airflow.
- Client Strategy: Translate business needs into technical blueprints and lead client communications.
- Governance: Implement security and compliance frameworks within Snowflake.
- Leadership: Mentor junior engineers and collaborate with our Snowflake, AWS and Anthropic partners.
Essential Requirements
- Experience: 8+ years in Data Engineering.
- Specialization: 4–5+ years of deep, hands-on expertise with Snowflake.
- Ownership: A proven track record of managing full-cycle projects (Discovery → Architecture → Production).
- Communication: Ability to explain complex technical solutions to non-technical stakeholders.
Why Join?
- Work with award-winning data pros.
- Total autonomy over problem-solving.
- High-visibility projects with massive organizations.
If you’re a Snowflake expert who loves solving hard problems, working with both Claude Code and IRL co-workers, we’re ready for you to join the team and start making an impact.
Skills Required
- 8+ years in Data Engineering
- 4-5+ years of deep, hands-on Snowflake expertise
- Design enterprise-scale Snowflake environments (multi-account, cost-optimized)
- Build and optimize data pipelines using Python, dbt, and Airflow
- Proven track record managing full-cycle projects (Discovery -> Architecture -> Production)
- Implement security and compliance frameworks within Snowflake
- Translate business needs into technical blueprints and lead client communications
- Mentor junior engineers and collaborate with Snowflake, AWS, and Anthropic partners
- Ability to explain complex technical solutions to non-technical stakeholders
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The Company
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