Mid-Level Data Engineer

Quality Digital

. Assist with database architecture for AI projects .

Posted 9/18/2026full-timeRemote • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in database architecture and data pipeline design, with proficiency in Python, PySpark, and SQL. Capable of implementing MLOps and AIOps architectures while optimizing infrastructure costs in AI projects.

Highest-signal resume keywords

Database ArchitectureData Pipeline DesignPython ProgrammingMLOps ArchitectureCloud Platform Frameworks

ATS Keywords

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Hard Skills

Database ArchitectureData Pipeline DesignPython ProgrammingPySparkSQLMLOpsAIOpsMachine Learning ImplementationComputer Vision SolutionsData Governance

Tools & Technologies

SalesforceAWSAzureGCPDatabricksDataikuMLflowCursorGitHub CopilotClaude Code

Certifications & Qualifications

Databricks CertificationAzure CertificationAWS Certification

Industry Keywords

Generative AIData IntegrationStructured DatabaseVector DatabaseUnstructured DatabaseSpec-Driven DevelopmentFinOps

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPySparkPythonSQL

About the role

Key responsibilities & impact

Assist with database architecture for AI projects
Assist with the implementation and maintenance of data pipelines for ingesting, storing, and processing large volumes of data
Ensure that data is available, accessible, and ready for data scientists and other stakeholders
Assist with prototyping and testing Generative AI models to solve specific business problems
Participate in the analysis of logs and usage metrics for AI models to identify failures, unexpected behavior, or opportunities to improve the user experience
Document processes, methodologies, and results related to AI projects
Participate in designing business process solutions using AI

Requirements

What you’ll need

Knowledge of database architecture and data pipeline design
Knowledge of data integration between systems
Knowledge of structured, vector, and unstructured database tools
Knowledge of Python, PySpark, and SQL
Knowledge of infrastructure and cloud platform frameworks, including Salesforce, AWS, Azure, GCP, Databricks, and Dataiku
Knowledge of technology stacks and development frameworks for LLMs, Agents, and Agentic AI
Knowledge of MLOps and AIOps architectures, including CI/CD for models, version control, and monitoring with MLflow
Knowledge of Cursor, GitHub Copilot, Claude Code, and Codex
Certifications in Databricks, Azure, or AWS are a plus
Knowledge of SAS is a plus
Experience implementing machine learning and computer vision solutions in data pipelines is a plus
Knowledge of data governance is a plus
Experience optimizing infrastructure costs (FinOps) in AI projects is a plus
Knowledge of Spec-Driven Development (SDD) for AI projects is a plus

Benefits

Comp & perks

An environment conducive to learning and professional growth
Performance reviews and feedback focused on continuous development
Meal and/or food allowance
Medical and dental insurance
Pharmacy partnerships offering discounts on medications
Childcare assistance in accordance with the applicable policy
Partnership with SESC, offering a variety of cultural and leisure activities
Partnerships for language and technology studies, as well as access to a course platform
Payroll-deducted loans at attractive rates
Financial education program
Corporate University and learning pathways
Referral program with opportunities for prizes and bonuses
Group life insurance