Senior Data Engineer – AI Automations, Azure, AWS

Lumini IT Solutions

Engenheiro de Dados atuando na construção e integração de pipelines em ambientes Azure e AWS. Responsável pela implementação de soluções de dados em um programa de inovação e modernização.

Posted 7/22/2026full-timeRemote • 🇧🇷 BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and integrating data pipelines within Azure and AWS environments, focusing on data ingestion, processing, and support for AI-driven automations. Proficient in implementing scalable architectures and ensuring data quality, security, and governance.

Highest-signal resume keywords

Data Pipeline DevelopmentCloud Solutions (AWS, Azure)ETL/ELT Process OptimizationDataOps and CI/CD ImplementationData Governance and Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLSparkData ModelingETL ToolsAPIs IntegrationRelational DatabasesNon-Relational DatabasesData ProcessingPerformance Optimization

Soft Skills

Verbal CommunicationWritten Communication

Tools & Technologies

Azure Data FactoryAWS GlueDatabricksSynapse AnalyticsAWS LambdaRedshiftGit

Certifications & Qualifications

DP-203 – Azure Data Engineer AssociateAWS Certified Data Analytics

Industry Keywords

Data EngineeringData LakesData WarehousesData MartsMachine Learning PipelinesEvent-Driven ArchitecturesLGPD Compliance

Tech Stack

Tools & technologies

Amazon RedshiftApacheAWSAzureDynamoDBETLKafkaMongoDBPostgresPythonSOAPSparkSQL

About the role

Key responsibilities & impact

We are looking for a Data Engineer to build and integrate data pipelines in Azure and AWS environments, ensuring data ingestion, processing, availability, and support for AI-driven automations.
The professional will be responsible for integrating APIs, ETLs, and existing databases, as well as implementing scalable architectures focused on analytics and decision support.
The project is part of a long-term program focused on modernization, innovation, Data, AI, Productivity, Optimization, and Process Automation.
Main Responsibilities:
Design and develop data ingestion pipelines from diverse sources (ETLs, APIs, relational and non-relational databases, files, telemetry sensors, etc.);
Integrate and consolidate data from multiple sources across Azure and AWS ecosystems, ensuring quality, consistency, and reliability;
Implement reference architectures for data processing and storage;
Create and manage Data Lakes, Data Warehouses, and Data Marts;
Develop and optimize ETL/ELT processes using tools such as Azure Data Factory, Databricks, Synapse Analytics, AWS Glue, AWS Lambda, and Redshift;
Ensure governance, security, and scalability of data pipelines;
Monitor and optimize data load performance, identify bottlenecks, and propose continuous improvements;
Work in direct collaboration with data scientists, functional analysts, and business stakeholders.

Requirements

What you’ll need

Solid experience as a Data Engineer building scalable pipelines;
Strong knowledge of cloud solutions on AWS (S3, Redshift, Glue, Athena) and Azure (Data Factory, Synapse, Databricks, Azure SQL, Blob Storage, Monitoring);
Experience integrating data via REST/SOAP APIs and processing data in real time;
Proficiency with relational databases (SQL Server, PostgreSQL) and non-relational databases (CosmosDB, DynamoDB, MongoDB);
Proficiency in Python, Spark, SQL, and PowerShell/Bash for data manipulation and engineering;
Experience with DataOps culture, code versioning (Git), and CI/CD pipelines for data;
Knowledge of data modeling, query tuning, and database performance optimization;
Understanding of security, governance, and compliance best practices (LGPD);
Strong verbal and written communication skills, with the ability to produce technical documentation and liaise with business teams.
Preferred / Nice-to-have:
Experience with event-driven architectures using AWS Kinesis, Azure Event Hub, or Apache Kafka;
Experience implementing Machine Learning pipelines and MLOps in cloud environments;
Microsoft certifications (e.g., DP-203 – Azure Data Engineer Associate) or AWS certifications (e.g., AWS Certified Data Analytics).

Benefits

Comp & perks

Work model: Remote (Home Office);
Contract type: PJ (contractor/freelancer);
Team working hours: business hours.
Important: We value diversity and inclusion and consider all candidates for our positions regardless of color, race, religion, gender and gender identity, nationality, disability, sexual orientation, ancestry, age, etc.