Senior Data Engineer

Team: Engineering

Location: Buenos Aires, Montevideo, Porto Alegre, Rosario, Maldonado, Rio de Janeiro, Fortaleza

Commitment: Contract | Remote

Workplace Type: remote

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: http://coderio.com

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.

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.