Develop and evolve ETL pipelines for data ingestion, transformation, and delivery.
Build integrations between different data sources, ensuring data quality, performance, and standardization.
Develop solutions using Python and Spark, working on AWS Cloud on the Databricks platform.
Monitor and improve production pipelines, ensuring reliability and process efficiency.
Collaborate with Analytics, Product, and Engineering teams to meet new data requirements.
Ensure data is available with high quality and low latency for consumption across the company.
Contribute to improvements in architecture, best practices, and the continuous evolution of data engineering.

Strong experience as a Data Engineer, developing and maintaining production data pipelines.
Experience with AWS, Python, Databricks, and batch and streaming ETL processes.
Knowledge of relational and non-relational databases, and familiarity with tools such as Kafka, Kibana, and Elasticsearch.
Good communication skills to collaborate with different areas and translate business needs into technical solutions.
English for reading and understanding technical documentation.
Experience at technology companies or high-scale fintechs.
Experience with Data Lakes and modern data architectures.
Experience working with large-volume data environments.
Able to document solutions and share knowledge with the team.

Health plan (no cost and no copay for you and your dependents)
Dental plan and life insurance
Flexible meal allowance via Caju (real freedom of use)
Complete well-being benefits: TotalPass (physical activity) + ZenKlub (mental health)
Annual performance-based bonus tied to goals and impact
Access to Skeelo Premium + book club with a monthly ebook
Childcare allowance + extended parental leave
Partnerships with language schools, Berlitz and Open English
Extended São Paulo holidays + paid year-end recess
Birthday day off

Senior Data Engineer

Key skills