Data Engineering Manager - AI-First Platform Leader Remote

Félix; Buenos Aires; Remote; ARS 232,274,000 - 325,183,000; Full time

Benefits offered by this job

Competitive salary

Initial stock options grant

Annual performance bonus

Health, dental, and vision plans

Work model: remote now, hybrid later

Continuous learning opportunities

Unlimited PTO

Paid parental leave

Growth opportunities in a dynamic env

Job summary

Félix is seeking a Data Engineering Manager to lead our core data team in a remote-friendly role. You will guide infrastructure projects, work across streaming and batch environments, and partner with our DBA team to ensure reliable data platforms. An AI-native mindset will help scale impact.

You will collaborate with cross-functional partners to deliver value, maintain high data quality, and implement scalable, secure data architectures in a modern cloud stack.

Qualifications

• Experience leading data engineering teams with hands-on coding.
• Strong proficiency in GCP, BigQuery, and analytics platforms.
• Practical use of dbt and real-time streaming with Flink or Dataflow.
• Comfort working with DBA teams and relational databases.
• Excellent written and spoken English.

Responsibilities

• Lead and mentor a Data Engineering squad and DBA team.
• Drive infrastructure projects across streaming and batch pipelines.
• Promote AI-native practices in code and platform ops.
• Ensure data quality, observability, and cost optimization.
• Align data work with business goals and product strategy.

Skills

Data Eng Leadership

GCP & BigQuery

dbt

Apache Flink

AI-powered mindset

DBA management

Strong communicator

Tools

PostgreSQL

MySQL

Job description

Félix is seeking a Data Engineering Manager to lead our core data team in a remote-friendly role. You will guide infrastructure projects, work across streaming and batch environments, and partner with our DBA team to ensure reliable data platforms. An AI-native mindset will help scale impact.

You will collaborate with cross-functional partners to deliver value, maintain high data quality, and implement scalable, secure data architectures in a modern cloud stack.