Senior Data Platform Engineer

Location: Remote - Brazil

To be considered for this position, you must reside in one of the following cities:

- São Paulo: São Paulo, Campinas, São José dos Campos

- Rio de Janeiro: Rio de Janeiro

- Minas Gerais: Belo Horizonte

- Paraná: Curitiba

- Santa Catarina: Florianópolis

About the role

We are seeking a Senior Data Platform Engineer to design and build scalable, data-intensive applications. This role requires expertise in ingesting and transforming large datasets, creating APIs for efficient data retrieval, and developing data products that drive business insights. You will be a key player in shaping our data platform while contributing to backend engineering initiatives.

The ideal candidate bridges the gap between traditional data engineering and backend development, building ETL pipelines, APIs, and data-driven solutions with a focus on performance and scalability.

What you'll be doing

- Design and implement ETL pipelines capable of processing terabytes of data efficiently.

- Develop and optimize APIs to support fast and reliable data retrieval, including both exact and partial matches.

- Architect and manage scalable storage solutions (e.g., Bigtable, BigQuery, ElasticSearch, or other NoSQL/SQL systems).

- Collaborate with teams to turn raw data into actionable products, driving insights and business value.

- Work closely with both internal and external stakeholders, including data science, product, and operation

- Document processes, architectures, and APIs. Mentor junior engineers and foster a culture of technical excellence.

What you'll need

- Advanced English proficiency (C1 level) is mandatory.

- 5+ years of experience building scalable backend systems, designing high-performance APIs, and processing large-scale datasets.

- Hands-on experience designing and building streaming pipelines using technologies like Apache Flink, Apache Beam, Airflow, and Apache Spark.

- Expertise in Go, Python, or Java, combined with a strong foundation in SQL and NoSQL databases (such as Bigtable, BigQuery, or DynamoDB) for scalable storage solutions.

- Proficiency with AWS or GCP infrastructure, containerization using Docker and Kubernetes, and managing CI/CD pipelines to support efficient deployments.

- Strong analytical skills with the ability to thrive in a fast-paced, team-driven environment and clearly communicate complex technical concepts.