Mid/Senior Data Engineer, Consulting

Job not on LinkedIn

🕒 August 19

🇧🇷 Brazil – Remote

⏳ Contract/Temporary

🟠 Senior

🚰 Data Engineer

👻 Ghost score 12%

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🗣️🇧🇷🇵🇹 Portuguese Required

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Logo of Datarisk

Datarisk

51 - 200 employees

Founded 2017

💼 Consulting

🏥 Healthcare

📣 Marketing

Consulting • Healthcare • Marketing

Datarisk is a data science and AI company that provides an MLOps platform, Model-as-a-Service (MaaS), credit-scoring solutions and AI agents to help organizations train, deploy and monitor machine learning models. It focuses on improving decision-making and risk management for financial institutions, fintechs and enterprises across sectors (marketing, supply chain, people analytics, retail and healthcare) by delivering cloud-hosted predictive models, specialized credit scores and consulting services. Datarisk positions itself as a B2B SaaS provider of machine learning and AI-driven products and services.

📋 Description

• Act as a consultant on strategic business projects focused on data engineering using Databricks • Identify and implement best practices for high-volume data ingestion, ensuring performance and availability • Optimize queries and data modeling to improve the efficiency of analytical queries • Develop and maintain ETL/ELT data pipelines to integrate multiple sources, ensuring data quality and governance • Design and implement Data Lakehouse architectures following the Medallion pattern (Bronze, Silver, Gold) • Support data modeling for modern Data Warehouses (Star Schema, Snowflake) • Apply best practices in Big Data environments, especially Databricks and Delta Lake • Use Delta Lake, Iceberg, Parquet and Avro within Lakehouse architectures • Ensure data governance, including access controls and versioning

🎯 Requirements

• Solid experience with Databricks and Delta Lakehouse architecture • Strong SQL skills and experience optimizing queries for distributed processing • Experience with ETL/ELT and designing scalable data architectures • Knowledge of incremental data pipelines (UPSERTS, MERGE, CDC) • Experience in analytical data modeling (Star Schema, Snowflake) • Experience with Databricks ingestions, including pipeline refactoring and performance tuning • Familiarity with Unity Catalog for governance and access control in Databricks • Knowledge of modern Data Warehouses (Databricks, Snowflake, BigQuery, Redshift) • Hands-on experience with AWS architectures, including S3, IAM, Glue and EMR • Experience provisioning and configuring Databricks clusters from scratch, including infrastructure, networking, permissions and integration with data catalogs

🏖️ Benefits

• Flexibility: remote-first team, work from anywhere • Health and dental plan with Bradesco • Conexa Saúde & Psicologia Viva • Wellhub (formerly Gympass) • Partnership with Open English • Caju: Home office allowance • Birthday day off • 22 business days per year of paid company recess • Contracting model: PJ (fixed monthly fee)

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