Job description

Profound is the fastest-growing AI marketing platform, used by 15% of the Fortune 500 including Comcast, Estée Lauder, and Walmart, and innovators like Ramp, MongoDB, and Figma. It is where marketing teams do the work: research, briefs, content, campaigns, reporting, all in one place, alongside agents that carry the load with them. Built on 2B+ real user prompts and growing, Profound’s data shows you what people ask AI and what the models say back. Profound's AI Marketer joins that data with deep context about our customers to find the opportunities worth acting on, and then puts agents to work: automating reporting, drafting content, auditing pages for readability, running competitive research. It measures what works and gets better every day. We are looking for an experienced Data Engineer to own and scale our data platform. You will maintain and optimize our pipelines, design new ingestion processes, and support the data needs of our product, data science, and go-to-market teams. This is a great opportunity for someone who enjoys working with modern data tooling, improving performance and reliability, and building the foundation for machine learning-powered features. WHAT YOU’LL DO - Maintain and improve data pipelines to keep data flowing reliably from ingestion to delivery - Optimize performance and costs across Snowflake, Clickhouse, AWS, dbt, and Dagster - Own data quality by implementing monitoring, alerting, and validation - Manage and extend infrastructure, including orchestration and CI or CD for data workflows - Support MLOps as machine learning models are developed and productionized - Be on call for critical pipelines and respond quickly to issues - Collaborate with data scientists, product managers, and engineers to launch new data products WHO YOU ARE - 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 - Strong problem-solving skills and a proactive mindset - Experience with or interest in MLOps and supporting machine learning workflows in production - Strong sense of ownership and accountability for data quality and reliability - Motivated by access to rare and interesting AI data based on real human interactions with large language models - Excited by the opportunity to own and shape Profound’s data platform at an early stage - Interested in working on meaningful problems at the intersection of AI and marketing - Comfortable in a fast-moving culture with autonomy, trust, and room to grow - Drawn to competitive compensation and meaningful equity LOCATION This is an on-site role based in our Union Square, NYC office, designed for builders who thrive on speed, iteration, and meaningful impact. For this role, the expected base salary range is $140,000 to $260,000. Comp may vary by location. Profound’s total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. Our recruiting team will share more details about the full compensation package and benefits as you move through hiring. #LI-DNI Note: All official communication from Profound will come from a @tryprofound.com email address. If you're contacted by anyone using a different domain, please disregard and report it as spam.

Requirements

Must-haves

This is a great opportunity for someone who enjoys working with modern data tooling, improving performance and reliability, and building the foundation for machine learning-powered features.
Maintain and improve data pipelines to keep data flowing reliably from ingestion to delivery
Optimize performance and costs across Snowflake, Clickhouse, AWS, dbt, and Dagster
Own data quality by implementing monitoring, alerting, and validation
Manage and extend infrastructure, including orchestration and CI or CD for data workflows
Support MLOps as machine learning models are developed and productionized
Be on call for critical pipelines and respond quickly to issues
Collaborate with data scientists, product managers, and engineers to launch new data products
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
Strong problem-solving skills and a proactive mindset
Experience with or interest in MLOps and supporting machine learning workflows in production
Strong sense of ownership and accountability for data quality and reliability
Motivated by access to rare and interesting AI data based on real human interactions with large language models
Excited by the opportunity to own and shape Profound’s data platform at an early stage
Interested in working on meaningful problems at the intersection of AI and marketing
Comfortable in a fast-moving culture with autonomy, trust, and room to grow
Drawn to competitive compensation and meaningful equity
This is an on-site role based in our Union Square, NYC office, designed for builders who thrive on speed, iteration, and meaningful impact.
Note: All official communication from Profound will come from a @tryprofound.com email address. If you're contacted by anyone using a different domain, please disregard and report it as spam.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aifigmagomachine learningawspythonsql

Platform: ashby
Effort: quick