Senior Data Engineer: Hr Ai Pipelines (Snowflake/Dbt)

Agileengine, Llc.; San Carlos de Bariloche; Remote; ARS 182,249,000 - 242,999,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Flexibility: 100% remote

Meaningful, modern projects

Collaborative culture

Well-being & support

Job summary

AgileEngine is seeking a Senior Data Engineer to design and maintain data pipelines powering Cloud Economics. You will build scalable ELT/ETL workflows using Python, SQL, dbt, Airflow across AWS services including Glue, Athena, and Aurora with Snowflake, focusing on performance, reliability, and cost efficiency.

You will collaborate with Engineering and Finance to drive cost optimization and provide usage-based insights for decision making, while ensuring data quality and auditability across

Qualifications

• 4+ years of data engineering experience.
• End-to-end ELT/ETL pipelines in cloud environments.
• Strong SQL and Python.
• Experience with orchestration tools (dbt, Airflow, Dagster).
• AWS data ecosystem including Glue, Athena, and Aurora.
• Experience with Snowflake.
• Strong data modeling and large-scale processing experience.
• Experience with CI/CD, version control, Terraform, and REST API integrations.
• Demonstrated ability to optimize data pipelines for performance and cost.
• Strong analytical skills with data validation, auditing, and troubleshooting production pipelines.

Responsibilities

• Design, build, and maintain the Cloud Economics team's data pipelines and automation systems.
• Build scalable datasets powering cloud cost visibility, attribution, and performance insights.
• Design data models and ingestion frameworks for large-scale telemetry and usage data.
• Develop tooling enabling cost-aware decision-making across product, engineering, and finance.
• Optimize data systems for performance, reliability, and cost efficiency.
• Partner with engineering and finance to support cost optimization initiatives and usage-based insights.
• Ensure data quality, validation, and auditability across end-to-end workflows.

Skills

SQL

Python

ELT/ETL pipelines

AWS data services

Snowflake

Data modeling

Orchestration tools

CI/CD

Terraform

REST APIs

Dagster/Airflow/dbt

Performance optimization

Cost optimization

Tools

dbt

Airflow

Dagster

AWS Glue

Amazon Athena

Amazon Aurora

Snowflake

Fivetran

Job description

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

- 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.

NICE TO HAVES

- 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

- Growth without limits : build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget

- Competitive compensation : get recognition that reflects your skills and impact, with regular performance and compensation reviews

- Flexibility : work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm

- Meaningful, modern projects : build impactful products using modern technologies alongside global teams and leading brands

- Collaborative culture : join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized

- Well-being & support : access local well-being programs and people-focused support tailored to your location

Requirements

- 4+ years of strong SQL and large-scale data ingestion/pipeline experience (batch ETL, orchestration, schema design).

- Direct or adjacent experience with digital advertising / DSP data (e.g., Amazon DSP, Amazon Advertising API, or comparable programmatic platforms).

- Working knowledge of AWS data services (RDS/Postgres, S3, ECS) sufficient to build within an existing cloud environment.

- Ability to contribute to application and backend work beyond pure ETL to support broader platform needs.

- Familiarity with, or ability to quickly evaluate, managed ELT tools (such as Fivetran) against custom builds.

- Ability to ramp into existing attribution and scoring logic so ingestion output aligns with downstream dashboard needs.