Data Engineer
Job Description
AirOps is an innovative AI-powered platform helping leading brands and agencies create content that resonates with both humans and AI agents. Backed by prominent investors including Unusual Ventures, Wing VC, and Founder Collective, AirOps is building the future of AI-enhanced marketing with hubs in San Francisco, New York, and Montevideo.
As a Data Engineer at AirOps, you'll be at the forefront of designing and maintaining the high-scale data infrastructure that powers their platform. This role combines technical expertise in data engineering with the excitement of working in a fast-growing startup environment. You'll be responsible for building robust data pipelines, ensuring data quality, and collaborating with cross-functional teams to drive insights and features.
The ideal candidate brings 4+ years of data engineering experience, with strong Python and SQL skills, and experience with modern data tools and cloud environments. You'll work with cutting-edge technologies and have the opportunity to shape the data infrastructure of a platform that's transforming how brands reach their audiences.
AirOps offers an attractive combination of startup equity, competitive benefits, and a flexible work environment. The company culture emphasizes extreme ownership, quality, curiosity, and making customers heroes. This is an excellent opportunity for a data engineer who wants to make a significant impact while working with a fun-loving, technically sophisticated team that moves fast and values innovation.
Responsibilities For Data Engineer
- Design, build, and maintain scalable ETL/ELT pipelines for ingesting and transforming large volumes of data
- Implement automated data validation, monitoring, and alerting to ensure quality and reliability
- Integrate diverse internal and external data sources into unified, queryable datasets
- Optimize storage and query performance for analytical workloads
- Collaborate with data scientists to productionize ML models and ensure they run reliably at scale
- Work with product and engineering teams to meet data needs for new features and insights
- Maintain cost efficiency and operational excellence in cloud environments
Requirements For Data Engineer
- 4+ years of experience in data engineering, ideally in AI, SaaS, or data-intensive products
- Strong fluency in Python and SQL
- Experience with modern data modeling tools such as dbt
- Experience with data warehouses and OLAP databases (e.g., Redshift, Snowflake, BigQuery, ClickHouse)
- Proven ability to design and maintain production-grade data pipelines in cloud environments (AWS, GCP, or similar)
- Familiarity with orchestration frameworks (Airflow, Dagster, Prefect)
- Comfort operating in fast-paced, ambiguous environments where you ship quickly and iterate
Benefits For Data Engineer
- Equity in a fast-growing startup
- Competitive benefits package tailored to your location
- Flexible time off policy
- Generous parental leave
- A fun-loving and (just a bit) nerdy team that loves to move fast!
