Senior Data Engineer, AWS + DataOps (Remote)

Arionkoder; Buenos Aires; Remote; ARS 139,364,000 - 201,304,000; Full time

Benefits offered by this job

100% remote

Long-term commitment

Autonomy and impact

International team

Career development

Job summary

Coderio seeks a Senior Data Engineer to design, build, and optimize scalable data platforms for large financial data volumes. You will shape high-performance data pipelines using Python, SQL, Spark on AWS, and collaborate with data science and product teams to deliver reliable solutions.

Reside in Argentina and participate in a remote-friendly culture, with opportunities to influence data governance, modern lakehouse architectures, and DataOps practices across global projects.

Qualifications

• 5+ years in Data Engineering or related roles with large-scale data systems.
• Strong Python and SQL skills for complex data processing.
• Hands-on Spark/PySpark, Delta Lake, and lakehouse architectures.
• AWS data services (S3, Glue, Athena, Lambda, EventBridge) prod experience.
• Experience with Airflow or similar DAG tools and Snowflake/Redshift/BigQuery.
• Real-time streaming design using Kafka or Kinesis; dbt experience helpful.
• DevOps/DataOps practices with Git, Docker, CI/CD, IaC (Terraform).
• Advanced English communication in technical contexts.

Responsibilities

• Design, build, and maintain high-throughput data pipelines for financial data.
• Scale cloud data warehouse and lakehouse architectures for large volumes.
• Collaborate with Data Scientists, Software Engineers, and PMs to translate needs.
• Implement data quality, monitoring, and data governance with compliance.
• Champion DataOps practices and IaC for data systems.

Skills

Python

SQL

Apache Spark

AWS

Data Mesh

Airflow

dbt

Kafka/Kinesis

Snowflake/Redshift/BigQuery

CI/CD / DevOps

Terraform / IaC

Tools

Databricks

Airflow

Snowflake

Redshift

BigQuery

Kafka

Kinesis

dbt

Terraform

Job description

Coderio seeks a Senior Data Engineer to design, build, and optimize scalable data platforms for large financial data volumes. You will shape high-performance data pipelines using Python, SQL, Spark on AWS, and collaborate with data science and product teams to deliver reliable solutions.

Reside in Argentina and participate in a remote-friendly culture, with opportunities to influence data governance, modern lakehouse architectures, and DataOps practices across global projects.