Senior Data Engineer – AI Automations, Azure, AWS

🕒 July 22

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 23%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Lumini IT Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2008

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Lumini IT Solutions is a technology and innovation company that focuses on accelerating business results. They offer managed IT services, cloud migration solutions, security information services, and application development. Lumini utilizes data science and artificial intelligence to enhance productivity and reduce costs while guiding their clients on a digital acceleration journey, addressing unique business challenges with high-impact solutions.

📋 Description

• 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

• 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

• 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.