The Role
Design and maintain scalable cloud data pipelines, ELT/ETL workflows, data models, and automation systems supporting cloud cost visibility and optimization. Use Python, SQL, dbt, Airflow, AWS services, and Snowflake to process large-scale telemetry and usage data. Optimize performance, reliability, and cost while ensuring data quality, validation, auditability, and production troubleshooting. Partner with Engineering and Finance stakeholders on cost-aware decision-making.
Summary Generated by Built In
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data Engineer to design and maintain data pipelines and automation systems that power cloud cost visibility, attribution, and performance insights for a Cloud Economics team. You will build scalable ELT/ETL workflows using Python, SQL, dbt, and Airflow across AWS services including Glue, Athena, and Aurora alongside Snowflake, optimizing for performance, reliability, and cost efficiency. The role partners closely with Engineering and Finance stakeholders to support cost optimization initiatives and usage-based decision-making.
WHAT YOU WILL DO
- Design, build, and maintain the Cloud Economics team's data pipelines and automation systems.
- Build and maintain scalable data pipelines and datasets that power cloud cost visibility, attribution, and performance insights.
- Design and implement data models and ingestion frameworks to support large-scale telemetry and usage data.
- Develop tooling that enables cost-aware decision-making across Product, Engineering, and Finance stakeholders.
- Optimize data systems for performance, reliability, and cost efficiency (query tuning, storage strategies, compute optimization).
- Partner with Engineering and Finance teams to support cost optimization initiatives and usage-based insights.
- Ensure data quality, validation, and auditability across end-to-end data workflows.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 4+ years of experience in Data Engineering roles.
- Strong Data Engineering foundation with proven experience building and maintaining end-to-end ELT/ETL pipelines in cloud environments.
- Strong SQL and Python.
- Experience with orchestration tools such as dbt, Airflow, or Dagster.
- AWS data ecosystem experience, including AWS Glue, Amazon Athena, and Amazon Aurora.
- Experience with Snowflake.
- Strong data modeling and large-scale data processing experience.
- Experience with CI/CD, version control, Infrastructure as Code (Terraform), and REST API integrations.
- Demonstrated ability to optimize data pipelines for performance and cost.
- Strong analytical skills with experience in data validation, auditing, and troubleshooting production pipelines.
- Upper-intermediate English level.
NICE TO HAVES
- Scala experience.
- FinOps Foundation Certification (Practitioner or Engineer).
- Experience with cloud cost optimization, tagging strategies, or cost monitoring.
- Experience with AWS and GCP. Experience with Datadog.
- Background in data platform or shared infrastructure engineering.
PERKS AND BENEFITS
- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Skills Required
- Authorization to work for any employer in the United States without visa sponsorship or sponsorship transfer
- 4+ years of experience in data engineering roles
- Experience building and maintaining end-to-end ELT/ETL pipelines in cloud environments
- Strong SQL and Python skills
- Experience with dbt, Airflow, or Dagster
- Experience with AWS Glue, Amazon Athena, and Amazon Aurora
- Experience with Snowflake
- Strong data modeling and large-scale data processing experience
- Experience with CI/CD, version control, Terraform, and REST API integrations
- Experience optimizing data pipelines for performance and cost
- Experience with data validation, auditing, and troubleshooting production pipelines
- Upper-intermediate English proficiency
- Scala experience
- FinOps Foundation Practitioner or Engineer certification
- Experience with cloud cost optimization, tagging strategies, or cost monitoring
- Experience with AWS and GCP
- Experience with Datadog
- Background in data platform or shared infrastructure engineering
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The Company
What We Do
AgileEngine is a privately held company established in 2010 that builds dedicated teams of designers and developers. We turn good ideas into awesome software that people actually want to use. Some of the biggest names and the hottest startups around the world chose us to build their tech.
