SR Data Engineer (AWS)

About Us

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)

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Design, build, and maintain high-throughput, low-latency batch and streaming data pipelines to ingest and process financial transactions from diverse global sources.

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Design, scale, and optimize cloud data warehouse and lakehouse architectures capable of handling massive volumes of structured and unstructured data.

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Collaborate with Data Scientists, Software Engineers, and Product Managers to understand business needs and translate them into scalable, reliable data solutions.

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Implement and enforce data quality frameworks, automated testing, monitoring, and alerting to ensure data integrity, reliability, high availability, and compliance with SLAs.

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Drive the adoption of DataOps practices , including CI/CD, workflow automation, and Infrastructure as Code (IaC) for data systems.

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Champion data governance, privacy, and security standards across data storage and compute layers, including GDPR/LGPD compliance.

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Mentor and guide junior and mid-level Data Engineers , promoting engineering excellence, best practices, and modern architectural patterns.

Requirements

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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.

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Strong proficiency in Python and SQL for complex data processing, optimization, and software development; Scala or Java experience is a plus.

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Hands-on experience with Apache Spark/PySpark, Delta Lake, and modern lakehouse architectures , including Data Mesh principles.

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Strong expertise in AWS data services , particularly S3, Glue, Athena, EventBridge, Firehose, and Lambda .

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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.

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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 .

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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.

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Advanced English proficiency is required , with the ability to communicate effectively in English in both technical and non-technical contexts.

Nice to Have

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Previous experience in Fintech, Payments, E-commerce, or other high-growth technology environments , particularly working with financial transactions or highly regulated data.

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Experience with Databricks and advanced cloud lakehouse architectures.

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Knowledge of data privacy, governance, and security frameworks , including GDPR/LGPD, as well as experience implementing secure data platforms.

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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-v