Cloud Data Engineer (AWS)

An AI-powered Economic Foundation Model company helping people and companies prosper through data-driven business insights.
$100,000 - $170,000
Data
Senior Software Engineer
Remote
5+ years of experience
AI · Enterprise SaaS

Description For Cloud Data Engineer (AWS)

Collective[i], a pioneering AI company backed by over 20 patents and founded by successful entrepreneurs with over $1B in prior exits, is seeking a Senior Data Engineer to join their innovative remote team. The company has invested over $100m in building a state-of-the-art platform that leverages AI to transform business outcomes and enhance prosperity at scale.

The role combines data engineering and AWS DevOps expertise, with a particular focus on deploying machine learning models using AWS SageMaker. You'll be working with cutting-edge technologies including Snowflake for analytics and data warehousing, while managing and optimizing the company's data infrastructure. The position offers an opportunity to work with a diverse team of scientists, engineers, and creative talent.

As a Senior Data Engineer, you'll be responsible for designing and maintaining ETL pipelines, building optimized data models, and ensuring high-quality data flow for analytics and reporting. You'll work extensively with AWS services, handle complex SQL transformations, and manage data orchestration through Apache Airflow. The role requires expertise in both traditional data engineering and modern cloud infrastructure, including CI/CD pipelines and infrastructure-as-code.

The ideal candidate will bring 5+ years of data engineering experience, with at least 3 years in AWS environments. Strong knowledge of AWS services, particularly SageMaker, and proficiency in Python and SQL are essential. You'll be joining a company that values diversity, innovation, and provides the freedom to work remotely while contributing to meaningful technological advancement.

Working at Collective[i] means being part of a culture that emphasizes curiosity, directness, and striving for the extraordinary. The company's impressive advisory board includes renowned economists, former Federal Reserve executives, and successful tech entrepreneurs. This is an excellent opportunity for someone who wants to work at the intersection of AI, data engineering, and cloud computing while making a significant impact on how businesses operate and succeed.

Last updated an hour ago

Responsibilities For Cloud Data Engineer (AWS)

  • Design, develop, and maintain ETL pipelines for reliable data flow and analytics
  • Build and optimize data models in Snowflake
  • Create and maintain complex SQL queries and transformations
  • Conduct orchestration and scheduling through Apache Airflow
  • Document data pipelines, architecture, and processes
  • Architect and maintain data science infrastructure on AWS
  • Deploy machine learning models on AWS SageMaker
  • Automate deployment using CI/CD pipelines and infrastructure-as-code
  • Manage AWS services (EC2, S3, RDS, VPC, etc.)
  • Set up and manage monitoring solutions

Requirements For Cloud Data Engineer (AWS)

Python
Java
Scala
  • Bachelor's or Master's degree in Computer Science, Data Engineering, or related field
  • 5+ years of Data Engineering experience with 3+ years in AWS
  • Strong knowledge of AWS services, especially SageMaker, Lambda, Glue, and Redshift
  • Experience with machine learning model deployment in AWS SageMaker
  • Proficiency in DevOps practices, CI/CD, containerization
  • Advanced SQL skills
  • Proficiency in Python, Java or Scala
  • Experience with Airflow for DAG management
  • Proficient in version control (GIT) and containerized deployment
  • Effective communication skills

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