Influur is building the world's first autonomous AI agent for influencer marketing, aiming to automate campaign execution from initiation to influencer activation with minimal human intervention. They aim to leverage proprietary data and direct influencer relationships to drive revenue and define the future of AI in influencer marketing.
Requirements
- Strong programming with Python and SQL.
- Expertise in data modeling and warehousing, including dimensional modeling and performance tuning.
- Experience designing and operating ETL and ELT pipelines with tools like Airflow or Dagster, plus dbt for transformations.
- Hands-on with batch and streaming systems such as Spark and Kafka, and with Lakehouse or warehouse tech on AWS or GCP.
- Proficiency integrating third-party APIs and datasets, ensuring reliability, lineage, and governance.
- Familiarity with AI data needs: feature stores, embedding pipelines, vector databases, and feedback loops that close the gap between model and outcome.
- High standards for code quality, testing, observability, and CI. Comfortable with Docker and modern cloud infra.
Responsibilities
- Strong programming with Python and SQL.
- Comfortable building from scratch and improving existing code.
- Expertise in data modeling and warehousing, including dimensional modeling and performance tuning.
- Experience designing and operating ETL and ELT pipelines with tools like Airflow or Dagster, plus dbt for transformations.
- Hands-on with batch and streaming systems such as Spark and Kafka, and with Lakehouse or warehouse tech on AWS or GCP.
- Proficiency integrating third-party APIs and datasets, ensuring reliability, lineage, and governance.
- Familiarity with AI data needs: feature stores, embedding pipelines, vector databases, and feedback loops that close the gap between model and outcome.
Other
- Young talent ready to go all in.
- Treats data as a product and ships improvements that users feel.
- Moves fast without breaking trust. You value contracts, schemas, and backward compatibility.
- Owns problems across the stack, from ingestion to modeling to serving.
- Communicates clearly with ML engineers, analysts, and business partners.
