Data Engineer

We work with the largest AWS premier partners around North America. Our expert consultants offer support when Amazon cannot solve problems and suggest solutions or implement projects in the AWS environment. Amazon uses us as a consultancy for service provision, including new product development, and we have a team of the world’s best cloud professionals focused on AWS, with ten consultants, among them four Brazilians.
Our team has 200 associates worldwide, including experienced cloud troubleshooting consultants. We are global partners of Azure and Google, covering almost all technologies. Our main purpose is cloud migration, with 95% of projects focused on this, and the other 5% on cloud-to-cloud migration projects.

WHAT YOU'LL DO:

• Design and optimize ETL/ELT processes using modern tools like Dbt, Glue, and custom scripts in Python, Scala, or Java;

• Create reliable data pipelines integrating data science and ML models with Spark, Airflow, and MLflow;

• Deploy scalable data storage and computation solutions like Data Lakes, Data Warehouses, and NoSQL databases to support advanced analytics and AI applications;

• Develop and maintain real-time data processing and analytics platforms with Kafka, Spark Streaming, Kinesis, Pub-Sub, and other streaming technologies for instant insights;

• Establish credibility and foster impactful customer relationships;

• Work remotely with other experts in the container ecosystem, data processing and analytics, cloud-native technologies, data science, and machine learning in a culturally diverse.

• Advanced English (At least between B2/C1);

• 5+ years of hands-on data engineering experience, specializing in large-scale processing and analytics systems;

• Expertise in cloud platforms specially AWS;

• Proficient in distributed systems and big data technologies like Spark, Hadoop, Kafka, and Airflow.

• Deep knowledge of production database architectures and data pipeline development, with strong software development skills;

• Deep understanding of data modeling, architecture, and storage strategies for structured and unstructured data.

• Strong problem-solving and communication skills, conveying technical concepts to non-technical stakeholders effectively.

• Demonstrated ability to quickly adapt to new technologies.

Mandatory Requirements:

• Minimum of 5 years of experience as a Data Engineer.
• Proficiency in Spark, Datalake, and AWS.
  
  

Nice to have: 

• Over 2 years of AI/ML model deployment in production, proficient in TensorFlow, PyTorch, and monitoring tools;

• Holds a Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field, with additional certifications in data science and machine learning.

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