Senior Data Engineer: Azure Data Platform (Remote/Flextime)

Zeo Consulting; Ciudad de Mendoza; Hybrid; ARS 136,310,000 - 196,892,000; Full time

Benefits offered by this job

Professional growth

Competitive USD-based compensation

Exciting projects

Flextime

Job summary

AgileEngine is seeking a Senior Data Engineer to replace a third-party data ingestion tool with an owned ETL pipeline. You will build and own the ingestion layer, ingesting from the Amazon API, DSP platforms, and related data sources.

You will collaborate with data science and infrastructure to align ingestion outputs with downstream dashboards and attribution models while leveraging AWS services and modern ML-ready pipelines.

Qualifications

• 4+ years of SQL and large-scale data ingestion experience with batch ETL and schema design.
• Working knowledge of AWS data services (RDS/Postgres, S3, ECS) within a cloud environment.
• Hands-on with Claude Code or similar tools and agents or MCP in real work.
• Ability to contribute to application/backend work beyond ETL to support the platform.
• Familiarity with or ability to evaluate ELT tools like Fivetran against custom builds.

Responsibilities

• Document current ingestion logic in the legacy tool: sources, endpoints, schemas, transforms.
• Build an ETL pipeline to replace legacy system ingesting from Amazon API and other DSP data sources.
• Evaluate off-the-shelf vs owned ETL solutions with Infrastructure Lead.
• Design the pipeline as a standalone owned system powering client dashboards.
• Provide AWS-based engineering support for app/backend work as needed.
• Coordinate with data science to ensure ingestion aligns with attribution/scoring models.
• Work within the existing AWS environment (ECS, S3, RDS) instead of new infra.

Skills

SQL

ETL

AWS

Claude Code

MCP

Tools

Fivetran

Amazon API

Job description

AgileEngine is seeking a Senior Data Engineer to replace a third-party data ingestion tool with an owned ETL pipeline. You will build and own the ingestion layer, ingesting from the Amazon API, DSP platforms, and related data sources.

You will collaborate with data science and infrastructure to align ingestion outputs with downstream dashboards and attribution models while leveraging AWS services and modern ML-ready pipelines.