Location: Argentina / Chile / CDMX

Modality: Remote

Who are they?

• A clean-technology organization focused on accelerating the energy transition through advanced energy storage solutions and proprietary technology.
• Operating internationally, they combine software, analytics, and infrastructure to deliver scalable, high-impact projects.
• A collaborative, engineering-driven culture that values ownership, technical excellence, agility, and innovation.

What will you do?

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time processing within AWS environments.
• Evolve and optimize a Data Lakehouse architecture, ensuring transactional integrity, high performance, and data consistency.
• Manage complex workflow orchestration and dependency logic using modern AWS-native and external tools.
• Implement robust data governance, security controls, and audit policies across the cloud ecosystem.
• Identify performance bottlenecks and optimize processes for speed, scalability, and cost-efficiency (FinOps mindset).
• Collaborate closely with Data Engineers and the Data Analyst to deliver production-ready datasets for reporting and decision-making.
• Ensure reliability through proactive monitoring, observability practices, automated alerts, and data quality validation.
• Act as a senior peer by mentoring colleagues, conducting code reviews, and elevating technical standards across the team.

What are they looking for?

• 5–8 years of experience in data engineering or related roles within cloud environments.
• Deep hands-on expertise with AWS data services such as Glue, Athena, Step Functions, Lambda, and Kinesis.
• Strong experience with Apache Iceberg and modern table formats in Lakehouse architectures.
• Expert-level proficiency in Python (PySpark / Python Shell) and advanced SQL (CTEs, window functions, execution plan tuning).
• Solid knowledge of data modeling best practices (Dimensional/Kimball) and ETL/ELT ecosystems.
• Experience preparing optimized data layers for BI and operational reporting tools.
• Practical experience with NoSQL (e.g., DynamoDB) and relational SQL databases.
• Familiarity with Infrastructure as Code (Terraform or CloudFormation).
• Strong ownership mindset, pragmatic decision-making, and collaborative communication skills.
• Nice to have: Airflow (MWAA), dbt, Airbyte, Fivetran, CI/CD automation for Glue/Lambda, and AWS certifications.

Why join them?

• Work on large-scale, high-impact energy infrastructure projects.
• Competitive salary.
• Professional development opportunities within a dynamic, international, and purpose-driven team leading the energy transition.