Data Engineer - Remote

Overview

We’re hiring a Data Engineer to design and maintain the high-scale data infrastructure that powers the AirOps platform. You will build robust ingestion, cleanup, and integration pipelines, ensuring that the data our customers rely on for brand visibility insights is accurate, reliable, and ready for analysis.

In Short

• 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

• 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

• 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!