Mid/Senior Data Engineer – Consulting

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🕒 January 15

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Datarisk

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

🤖 Artificial Intelligence

☁️ SaaS

💳 Fintech

Artificial Intelligence • SaaS • Fintech

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 the Databricks platform; • Identify and implement best practices for high-volume data ingestion, ensuring performance and data availability; • Work on query optimization and data modeling to improve the efficiency of analytical queries; • Develop and maintain data pipelines (ETL/ELT) to integrate multiple sources, ensuring data quality and governance; • Design and implement Data Lakehouse architectures, applying the Medallion pattern (Bronze, Silver, Gold); • Support data modeling for modern Data Warehouses (Star Schema, Snowflake); • Explore best practices in Big Data environments, especially in the context of Databricks and Delta Lake; • Use open formats such as Delta Lake, Iceberg, Parquet and Avro for building and governing modern Lakehouse architectures; • Ensure data governance, including access control 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 scalable data architectures; • Knowledge of incremental data pipelines (UPSERTS, MERGE, CDC); • Experience in analytical data modeling (Star Schema, Snowflake); • Experience with Databricks workloads, including pipeline refactoring and performance tuning; • Advantage: Familiarity with Unity Catalog for governance and access control in Databricks; • Knowledge of modern Data Warehouses (Databricks, Snowflake, BigQuery, Redshift); • Experience with AWS architectures, with strong knowledge of services such as S3, IAM, Glue and EMR; • Experience provisioning and configuring Databricks clusters from scratch, including infrastructure, networking, permissions and integration with data catalogs.

🏖️ Benefits

• Flexibility! Our team is remote — work from anywhere; • Bradesco health and dental plan; • Conexa Saúde & Psicologia Viva; • Wellhub (formerly Gympass); • Partnership with Open English; • Caju: Home Office allowance; • Birthday day off; • 22 working days/year of paid leave; • Hiring model: PJ (fixed monthly fee).