Senior Data Engineer - Cloud Economics & ELT (Remote)
AgileEngine, LLC.
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Benefits offered by this job
Job summary
AgileEngine, LLC. is seeking a Senior Data Engineer to design and maintain data pipelines powering the Cloud Economics team.
You will build ELT/ETL workflows using Python, SQL, dbt, and Airflow across AWS services (Glue, Athena, Aurora) and Snowflake, focusing on performance, reliability, and cost efficiency. You will partner with Engineering and Finance to support cost optimization and usage-based decision-making, ensuring data quality and auditable end-to-end workflows across large-scale
Qualifications
- It must be authorized to work in the US; no sponsorship expected.
- 4+ years in data engineering roles with end-to-end ELT/ETL in cloud.
- Strong SQL and Python foundations.
- Experience with orchestration tools: dbt, Airflow, or Dagster.
- Hands-on with AWS data services (Glue, Athena, Aurora) and Snowflake.
- Experience with data modeling, CI/CD, Terraform, and REST APIs.
Responsibilities
- Design, build, and maintain data pipelines and automation for Cloud Economics.
- Develop scalable pipelines for cloud cost visibility and performance insights.
- Model data schemas and ingestion for telemetry and usage data at scale.
- Create tooling for cost-aware decision making across stakeholders.
- Optimize pipelines for performance, reliability, and cost.
- Collaborate with Engineering and Finance on cost optimization initiatives.
- Ensure data quality, validation, and auditability across end-to-end workflows.
Skills
Tools
Job description
AgileEngine, LLC. is seeking a Senior Data Engineer to design and maintain data pipelines powering the Cloud Economics team.
You will build ELT/ETL workflows using Python, SQL, dbt, and Airflow across AWS services (Glue, Athena, Aurora) and Snowflake, focusing on performance, reliability, and cost efficiency. You will partner with Engineering and Finance to support cost optimization and usage-based decision-making, ensuring data quality and auditable end-to-end workflows across large-scale
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