Remote Senior Data Engineer - Marketing Data Pipelines + Ai

Unavailable; Buenos Aires; A distancia; ARS 107.614.000 - 184.482.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% remote

Long-term commitment

Strategic, high-visibility role

Collaborative international team

Career development and growth

Descripción de la vacante

Coderio designs and delivers scalable data platforms for global clients, with a product mindset and a remote-first approach. We seek a Senior Data Engineer in Argentina to design and optimize high-performance data systems handling financial and transactional data.

The ideal candidate brings strong Python/SQL, Spark, AWS, and Data Mesh experience, with a track record of production-grade systems in fast-paced environments. Candidates must reside in Argentina, Brazil, or Uruguay.

Formación

• 5+ years in Data Engineering or related roles managing high-volume, production-grade data systems.
• Strong Python and SQL for data processing and software development; Scala/Java a plus.
• Experience with Spark/PySpark, Delta Lake, and modern lakehouse architectures.

Responsabilidades

• Design, build, and maintain high-throughput data pipelines ingesting financial transactions.
• Scale cloud data warehouse and lakehouse architectures for massive data volumes.
• Collaborate with data scientists, engineers, and product managers to translate requirements.

Conocimientos

Python

SQL

Apache Spark

AWS

Data Mesh

Airflow

dbt

CI/CD

Docker

Terraform

Herramientas

Delta Lake

Snowflake/Redshift/BigQuery

Kubernetes

Descripción del empleo

Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end. We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.

More information:

We are looking for a Senior Data Engineer to design, build, and optimize scalable, high-performance data platforms supporting large volumes of financial and transactional data. The ideal candidate has strong expertise in Python, SQL, Apache Spark, AWS, and modern data engineering architectures, with proven experience working with production-grade systems in fast-paced environments.

Candidates must reside exclusively in Argentina, Brazil, or Uruguay.

What You Can Expect (Responsibilities)

• Design, build, and maintain high-throughput, low-latency batch and streaming data pipelines to ingest and process financial transactions from diverse global sources.
• Design, scale, and optimize cloud data warehouse and lakehouse architectures capable of handling massive volumes of structured and unstructured data.
• Collaborate with Data Scientists, Software Engineers, and Product Managers to understand business needs and translate them into scalable, reliable data solutions.
• Implement and enforce data quality frameworks, automated testing, monitoring, and alerting to ensure data integrity, reliability, high availability, and compliance with SLAs.
• Drive the adoption of DataOps practices, including CI/CD, workflow automation, and Infrastructure as Code (IaC) for data systems.
• Champion data governance, privacy, and security standards across data storage and compute layers, including GDPR/LGPD compliance.
• Mentor and guide junior and mid-level Data Engineers, promoting engineering excellence, best practices, and modern architectural patterns.

Requirements

• 5+ years of experience in Data Engineering, Big Data, or related Software Engineering roles, with a proven track record managing high-volume, production-grade data systems in fast-paced environments.
• Strong proficiency in Python and SQL for complex data processing, optimization, and software development; Scala or Java experience is a plus.
• Hands‑on experience with Apache Spark/PySpark, Delta Lake, and modern lakehouse architectures, including Data Mesh principles.
• Strong expertise in AWS data services, particularly S3, Glue, Athena, EventBridge, Firehose, and Lambda.
• Solid experience with data orchestration and warehousing technologies, including Apache Airflow or similar DAG-based tools and platforms such as Snowflake, AWS Redshift, or Google BigQuery.
• Experience designing real-time streaming architectures using technologies such as Apache Kafka or AWS Kinesis, as well as familiarity with modern data transformation and modeling tools such as dbt.
• Strong knowledge of DevOps/DataOps practices, including Git, Docker, CI/CD pipelines (GitHub Actions, GitLab CI, or similar), Infrastructure as Code, and cloud platforms such as AWS or GCP.
• Advanced English proficiency is required, with the ability to communicate effectively in English in both technical and non-technical contexts.

Nice to Have

• Previous experience in Fintech, Payments, E-commerce, or other high-growth technology environments, particularly working with financial transactions or highly regulated data.
• Experience with Databricks and advanced cloud lakehouse architectures.
• Knowledge of data privacy, governance, and security frameworks, including GDPR/LGPD, as well as experience implementing secure data platforms.
• Experience with Infrastructure as Code tools such as Terraform, advanced DataOps automation, and mentoring Data Engineers or contributing to technical architecture decisions.

Benefits

• 100% remote
• Long-term commitment, with autonomy and meaningful impact
• Strategic, high-visibility role within a modern engineering culture
• Collaborative international team with strong technical leadership
• Career development and growth opportunities within Coderio

Why join Coderio?

At Coderio, we value talent and excellence. While we are primarily a remote-first company, this specific strategic role offers the opportunity to work directly on-site to drive high-stakes initiatives. We are passionate about technology, collaboration, and fair compensation. We offer an inclusive and challenging environment with real growth opportunities. If you are motivated to design solutions that make a difference, we are waiting for you.