Data Science

Must-Haves: Python, SQL, and PySpark. Data platform, lake, and warehouse architecture (BigQuery, Dataproc, Dataflow, Dataplex, Composer), along with modern analytical engines (Databricks, Snowflake). Relational DBs (PostgreSQL, SQL Server, Oracle). Streaming and batch processing (e.g., Kafka, PubSubs). Familiarity with NoSQL DBs (MongoDB, Cassandra, HBase, DynamoDB, Redis, Bigtable) and BI tools (Looker, Power BI, Tableau, QlikSense, QlikView). 

Languages: Fluent English / Nice to have: Portuguese

Nice-to-Haves: Scala, Apache Beam, and Hadoop. IaC and CI/CD/DevOps tools (Terraform, Git actions, GitLab, Azure DevOps, Jenkins). Infrastructure components (Linux/Bash, VMs, GKE, Kubernetes). AI / ML, LLMs, GenAI, or ML Ops