Senior Data Engineer

Experience and Skills

• 6+ years of experience in data engineering or related data-focused roles.
  Professional Spanish for daily collaboration.
  Hands-on production experience building and operating data pipelines on AWS.
  Advanced SQL and relational data modeling skills.
  Strong experience with Power BI for business reporting and visualization.
  Production experience with Python for data processing.
  Strong collaboration, stakeholder communication, reliability and adaptability.

Key Responsibilities

• Ingest, process, and transform data from multiple source systems into AWS-based data platforms.
• Design and maintain integration flows for data movement between source and target systems, adhering to established standards.
• Ensure data delivered to Power Apps applications and Power BI reports meets quality, consistency, and timeliness requirements.
• Partner with product and business teams to identify data needs, evaluate source systems, and assess technical constraints.
• Build data engineering solutions aligned with internal data strategy while maintaining autonomy and meeting committed timelines.

Benefits

Work on high-impact data initiatives for a global resources and industrial operations company. This is a fully remote, full-time contractor role for candidates based in LATAM, paid monthly in USD.

You will join an established data engineering team as an individual contributor and collaborate directly with product and business stakeholders while working on reliable production data systems.

Power Apps.
AWS Lambda, S3 and Glue.
Apache Airflow.
dbt.
Snowflake.
Data quality, observability and lineage.
CI/CD for data pipelines.

This role is part of the data engineering function at a global resources and industrial operations company. You will join an existing team as a hands-on individual contributor, building and operating end-to-end data pipelines on AWS.

The work covers multi-source ingestion, transformation, and reliable delivery into Power Apps applications and Power BI reporting used by business and operations teams. The objective is to improve data availability, quality, and operational decision-making across the organization. You will collaborate closely with product and business stakeholders; this is not a people-management role.