over 1 year ago
Base Salary
$160k - $250k/yr
Responsibilities
- Maintain and improve reliable production data pipelines from ingestion through delivery.
- Design new data-ingestion processes and support data needs for product, data science, and go-to-market teams.
- Optimize performance and costs across Snowflake, ClickHouse, AWS, dbt, and Dagster.
- Implement monitoring, alerting, and validation to maintain data quality.
- Manage and extend orchestration and CI/CD infrastructure for data workflows.
- Support MLOps and the development and productionization of machine-learning models.
- Participate in on-call coverage and respond to critical pipeline issues.
- Collaborate with data scientists, product managers, and engineers to launch data products.
Requirements
- Proven experience designing, building, and maintaining production data pipelines.
- Proficiency in Python and SQL.
- Hands-on experience with dbt, orchestration frameworks such as Dagster, Airflow, or Prefect, and AWS.
- Familiarity with Snowflake, ClickHouse, or other modern data warehouses.
- Experience with or interest in MLOps and production machine-learning workflows.
- Strong problem-solving skills, ownership, accountability, and focus on data quality and reliability.
- Comfort working autonomously in a fast-moving environment.
Benefits
- On-site role based in the Union Square, NYC office.
- Meaningful equity.
- Full range of benefits and perks.
About Profound
Profound builds a SaaS marketing intelligence platform that helps enterprise brands measure and improve how they appear in AI-driven discovery across tools like ChatGPT and Perplexity. The product delivers real-time visibility analytics, competitive intelligence, and optimization insights for search-like AI channels. The company is privately held, headquartered in New York, and is Series C–funded.