Senior Data Engineer AWS

Coderio; Porto Alegre; Remote; BRL 320,000 - 520,000; Full time

Benefits offered by this job

100% remote

Long-term commitment with autonomy

Job summary

Coderio designs and delivers scalable data platforms for global clients. The Senior Data Engineer will build high-performance pipelines for financial data and work with Python, SQL, Spark, and AWS.

The role emphasizes DataOps, governance, and modern lakehouse architectures, with opportunities to mentor teammates and influence design decisions.

Qualifications

• 5+ years in Data Engineering or related roles for high-volume data systems.
• Proficient in Python and SQL; Scala/Java a plus.
• Experience with Spark/PySpark, Delta Lake, lakehouse architectures.

Responsibilities

• Design, build, and maintain high-throughput data pipelines for financial data.
• Scale cloud data warehouse and lakehouse architectures for large data volumes.
• Collaborate with data scientists and engineers to translate requirements into scalable solutions.
• Enforce data quality, testing, monitoring, and SLAs with data governance and security.
• Drive DataOps practices, including CI/CD and IaC for data systems.
• Mentor junior engineers and promote best practices and modern architectures.

Skills

Python

SQL

Spark

AWS

Data modeling

Data governance

CI/CD

ETL

Airflow

Scala/Java

English

Education

Bachelor's degree in Computer Science or related field

Tools

Delta Lake

Snowflake

Redshift

BigQuery

Airflow

Databricks

Docker

Terraform

Kinesis

Job description

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. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.