Lead Data Engineer

AirOps

full-time

Posted on: 9/28/2025

Location Type: Hybrid

Location: New York City • California, New York • 🇺🇸 United States

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Senior

AirflowAmazon RedshiftAWSBigQueryCloudETLGoogle Cloud PlatformPythonSQL

About the role

Design, build, and maintain scalable ETL 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
Build robust ingestion, cleanup, and integration pipelines to ensure accurate, reliable data ready for analysis

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

Tip: use these terms in your resume and cover letter to boost ATS matches.

ETLdata validationdata transformationdata modelingPythonSQLdata warehousesOLAP databasescloud environmentsorchestration frameworks

collaborationproblem-solvingadaptabilitycommunicationoperational excellence