Data Engineer – Mid-Level

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. Design and build ETL/ELT pipelines in Databricks or using open-source strategies, ingesting and processing data within a medallion architecture on Delta Lake .

Posted 10/2/2026contractRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building ETL/ELT pipelines using Databricks and open-source strategies, with a strong focus on data curation, compliance with LGPD, and integration of databases with APIs. Proficient in automating processes and ensuring data quality within a medallion architecture.

Highest-signal resume keywords

Advanced PythonSQLDatabricksData ModelingLGPD Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DesignData CurationVector IndexingData Quality TestingVersioningUnstructured Data ProcessingMedallion ArchitectureEmbedding GenerationIncremental Index UpdatesData Standardization

Tools & Technologies

DatabricksDelta LakePySparkSpark SQLGitCI/CDAzureAWSGCPMLflow

Certifications & Qualifications

Databricks Data Engineer AssociateDatabricks Data Engineer Professional

Industry Keywords

InsuranceFinancial ServicesSensitive Data HandlingUnity CatalogMosaic AIDelta Live TablesLakeflowAuto LoaderTerraformDatabricks Asset Bundles

Tech Stack

Tools & technologies

AWSAzureETLGoogle Cloud PlatformPySparkPythonSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Design and build ETL/ELT pipelines in Databricks or using open-source strategies, ingesting and processing data within a medallion architecture on Delta Lake
Ingest and standardize PDF documents and images with metadata
Perform data curation and anonymization in compliance with Brazil’s LGPD, generating datasets for RAG, few-shot learning, and testing
Build and operate vector indexing, including chunking, embedding generation, incremental index updates, and versioning
Prepare versioned datasets (golden sets) for accuracy evaluation and benchmarking
Structure feedback-loop persistence and feed the Quality and SLA Dashboard
Integrate databases with inference services and APIs to other systems, taking performance, cost, monitoring, and alerting into account
Automate processes using Workflows/Jobs, CI/CD, and data quality tests

Requirements

What you’ll need

Advanced Python and SQL
Data modeling and medallion architecture / Lakehouse
Experience with unstructured data pipelines (PDFs, images, and text) and preparing data for RAG
Familiarity with vector databases and embeddings (Databricks Vector Search, pgvector, or similar)
Data quality, data testing, and versioning
Hands-on Databricks experience: Delta Lake, Workflows/Jobs, notebooks, PySpark, and Spark SQL
Git and CI/CD
Experience in a cloud environment (Azure, AWS, or GCP)
Knowledge of LGPD and sensitive data handling
Unity Catalog in a governed environment (preferred)
MLflow, Databricks Model Serving, and Mosaic AI (preferred)
Delta Live Tables / Lakeflow and Auto Loader (preferred)
Experience in the insurance or financial services industry (preferred)
Terraform or Databricks Asset Bundles (preferred)
Databricks Data Engineer Associate or Professional certification (preferred)

Benefits

Comp & perks

Anywhere Office: geographic flexibility to work from the location that makes the most sense for you, depending on the project
Discount partnerships
Employee referral program with rewards
Birthday day off
TotalPass/Gympass
Health and wellness initiatives
Opportunities to relax at our offices, with beanbags, a pool table, video games, a lounge, a fully equipped kitchen, and coffee