Sales Engineer

About The Job

Sifflet is a leading data observability platform helping modern data teams trust their data and move faster. We enable organizations to monitor data quality, reliability, and lineage across the modern data stack, empowering data engineers, analysts, and business teams to make better decisions with confidence. We are a fast-growing, international company expanding our presence in North America, and this is an opportunity to be on the ground floor of that growth.

Role

We're hiring a Sales Engineer in the US—a highly autonomous, sales-oriented technical expert who will play a critical role in building our North American business. This is a presales-heavy role (~80%), where you'll partner closely with Account Executives to win new business, run technical evaluations, and shape how prospects understand data observability. You'll also own implementations for new customers, ensuring a smooth transition from sale to value realization. This is a unique opportunity to combine technical depth, sales influence, and ownership, while helping define how Sifflet scales in the US.

Requirements

• 3–5 years in a Solutions Engineer, Sales Engineer, or similar technical presales role.
• Experience in a startup or high-growth environment is a strong plus.

Technical Skills

• Strong familiarity with the modern data stack (e.g. Snowflake, BigQuery, Redshift, dbt, Airflow, Databricks, Fivetran, Looker, etc.).
• Proficient in SQL and comfortable with Python or similar scripting languages.
• Solid understanding of data pipelines, cloud environments (AWS/GCP/Azure), and APIs.

Sales Mindset

• Comfortable owning technical aspects of complex sales cycles.
• Strong storytelling and demo skills—connect technical features to business value.
• Able to navigate ambiguity and drive deals forward proactively.

Autonomy & Ownership

• Thrives in a remote, startup environment with minimal oversight.
• Excited about building from scratch and being the first on the ground.
• Hightly organized and able to manage multiple deals and implementations in parallel.