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Solutions Architect – Enterprise
| Company | dbt Labs |
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| Location | New York, NY, USA |
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| Salary | $180000 – $230000 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Mid Level, Senior |
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Requirements
- 4+ years of sales engineering, solutions architecture, or consulting in data operations, analytics, or BI
- A strong foundation in pre-sales or technical sales, with the ability to quickly learn new technologies—prior experience with dbt is not required
- A solid technical background, with experience in SQL, ETL, and data modeling
- A firm understanding of and ability to discuss modern data warehousing architectures
- Ability to gather and translate technical and business requirements into concrete solutions
- Excellent verbal, written, and in-person communication skills to discuss complex topics with both technical and non-technical audiences
- Ability to operate in an ambiguous and fast-paced work environment
- A passion for being an inclusive teammate and involved member of the community
Responsibilities
- Become an expert in designing enterprise-grade data pipelines with dbt Cloud
- Work hand-in-hand with sales to communicate the technical value of the dbt Labs suite of products
- Guide customers through proof-of-concept implementations and facilitate trials of dbt Cloud
- Work with engineering to deploy dbt Cloud in private clouds for enterprise clients
- Own the full customer lifecycle from pre-sale evaluation to product adoption and expansion
- Work with product to build and maintain the dbt Cloud enterprise roadmap
- Build close relationships with our Partners (including companies like Snowflake, AWS, and Databricks) and enable them to adopt and implement dbt for their clients
- Be an active member of the dbt community
Preferred Qualifications
- Prior experience working at an analytics, ETL, BI, and/or open-sourced software
- Knowledge of or prior experience with dbt
- Experience with Data Modeling methods such as dimensional, data vault, Kimball, 3NF
- Experience with Data warehousing tooling (Snowflake, Databricks, etc.)
- Experience with leading the technical aspects of the sales cycle, including discovery, solution demos, value articulation, scoping proof-of-value (POV) engagements, executive-level POCs, and final readouts
