Agile Engine 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 Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling.

WHAT YOU WILL DO

- Develop and implement tooling and datasets that drive telemetry-driven cost attribution and performance-informed financial modeling, enabling product, engineering, analyst, and finance stakeholders to make faster, data-driven decisions and trust the data.
- Build and maintain data pipelines and tooling that provide cost transparency, surface optimization opportunities, and support committed use discount modeling and management.

MUST HAVES

- 4+ years of experience in Data Engineering roles .
- Hands-on experience with SQL, Python, Spark, and Scala .
- Hands-on experience with workflow orchestration tools such as dbt, Airflow, and Dagster .
- Hands-on experience with AWS (Glue, Aurora, Athena), GCP, and Snowflake .
- Experience architecting and enhancing the long-term maintainability of end-to-end ELT/ETL data pipelines, including data modeling and schema maturity.
- Exposure to CI/CD development processes, Infrastructure as Code (Terraform ), and REST API programming.
- Strong attention to detail, analytical skill, and comprehensive data auditing and end-to-end validation skills.
- Ability to explain technical concepts to non-technical audiences.

NICE TO HAVES

- Experience with Fin Ops teams or cost optimization job duties.
- Fin Ops Practitioner or Fin Ops Engineer certification.
- Experience with Datadog API endpoints.
- Experience with Go.

PERKS AND BENEFITS

- Professional growth: Accelerate your professional journey with mentorship, Tech Talks, 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.

Job Description

Agile Engine 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 Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling.

WHAT YOU WILL DO

- Develop and implement tooling and datasets that drive telemetry-driven cost attribution and performance-informed financial modeling, enabling product, engineering, analyst, and finance stakeholders to make faster, data-driven decisions and trust the data.
- Build and maintain data pipelines and tooling that provide cost transparency, surface optimization opportunities, and support committed use discount modeling and management.

MUST HAVES

- 4+ years of experience in Data Engineering roles .
- Hands-on experience with SQL, Python, Spark, and Scala .
- Hands-on experience with workflow orchestration tools such as dbt, Airflow, and Dagster .
- Hands-on experience with AWS (Glue, Aurora, Athena), GCP, and Snowflake .
- Experience architecting and enhancing the long-term maintainability of end-to-end ELT/ETL data pipelines, including data modeling and schema maturity.
- Exposure to CI/CD development processes, Infrastructure as Code (Terraform ), and REST API programming.
- Strong attention to detail, analytical skill, and comprehensive data auditing and end-to-end validation skills.
- Ability to explain technical concepts to non-technical audiences.
- Upper-intermediate English level.





NICE TO HAVES

- Experience with Fin Ops teams or cost optimization job duties.
- Fin Ops Practitioner or Fin Ops Engineer certification.
- Experience with Datadog API endpoints.
- Experience with Go.

PERKS AND BENEFITS

- Professional growth: Mentorship, Tech Talks, and personalized growth roadmaps.
- Competitive compensation : USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Versátil schedule with remote and office options.

Requirements
5+ years of professional experience in Data Engineering or Data Platform Engineering Strong hands-on experience operating and developing solutions on Snowflake, including data-layer design, warehouse performance, access patterns, and production troubleshooting.
Advanced SQL skills and strong experience with dbt for transformation, testing, documentation, lineage, and controlled deployment. Experience operating managed ingestion tools such as Fivetran or HVR and supporting custom data-ingestion pipelines.
Hands-on experience with AWS data services, particularly S3 and event-driven or file-based ingestion patterns. Experience orchestrating and troubleshooting data workloads with Argo Workflows on Kubernetes, or comparable workflow-orchestration technologies.
Proficiency in Python or a comparable language for data engineering, automation, and operational tooling. Strong understanding of data modeling, pipeline dependencies, schema evolution, backfills, data validation, and production data quality.
Experience with observability, logging, alerting, and incident-management practices for production data platforms. Demonstrated ability to lead complex incident resolution, perform root-cause analysis, and convert findings into preventive improvements.
Ability to make well-reasoned technical decisions, identify tradeoffs, estimate work, and guide improvements across a complex platform. Experience mentoring engineers and collaborating effectively with Cloud / Dev Ops, Analytics, Security, Governance, and business stakeholders.

Strong written and verbal English communication skills, with the ability to work directly with client stakeholders. Availability to work from 9:00 AM to 6:00 PM Pacific Time and participate in an agreed on-call rotation.

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📌 Senior Remote Data Engineer — Marketing Analytics & Pipelines (Rosario)
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