Senior Data Engineer: Remote & Flexible Hours

AgileEngine; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Remote work with flexible hours

Meaningful, modern projects

Collaborative culture

Well-being programs

Job summary

AgileEngine is seeking a Senior Data Engineer to architect, build, and scale a modern data platform. You will design production-grade ETL/ELT pipelines, optimize Snowflake schemas, and implement robust DataOps practices.

You will orchestrate workflows using Airflow, Prefect, or Dagster, integrate REST APIs and event-driven sources, and apply CI/CD, Docker, and automated testing to data repositories. The role emphasizes clean, well-tested Python code and a strong focus on data reliability and

Qualifications

• 4+ years of Data Engineer experience.
• Strong Python fundamentals, modular, well-tested code.
• Advanced SQL and data modeling skills.
• Hands-on Snowflake data warehousing experience.
• Experience with Airflow/Prefect/Dagster orchestration.
• Experience integrating REST APIs and event-driven data sources.
• Knowledge of CI/CD, Docker, and Git.

Responsibilities

• Design, build, and maintain reliable ETL/ELT workflows from diverse sources.
• Design production-ready Snowflake schemas for analytics.
• Ingest data via REST APIs, events, and batch sources.
• Maintain and expand orchestration pipelines with Airflow/Prefect/Dagster.
• Implement automated data quality checks, lineage, and alerts.
• Apply DataOps practices with CI/CD and IaC basics.
• Write clean, well-documented Python code and enforce testing.

Skills

Python

SQL & Modeling

Snowflake

Airflow/Prefect

REST APIs

CI/CD & Docker

Git

Data Quality/Lineage

DataOps

English Proficiency

Tools

dbt

Dagster

Airflow

Job description

AgileEngine is seeking a Senior Data Engineer to architect, build, and scale a modern data platform. You will design production-grade ETL/ELT pipelines, optimize Snowflake schemas, and implement robust DataOps practices.

You will orchestrate workflows using Airflow, Prefect, or Dagster, integrate REST APIs and event-driven sources, and apply CI/CD, Docker, and automated testing to data repositories. The role emphasizes clean, well-tested Python code and a strong focus on data reliability and