Take2 Consulting, LLC
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer on a contract basis, focusing on building AWS-based data pipelines and analytics. Key skills include AWS services, big data technologies, and DevOps practices. Requires experience in data architecture and collaboration with data scientists.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 10, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
St Louis, MO
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🧠 - Skills detailed
#AI (Artificial Intelligence) #DevOps #Big Data #ML (Machine Learning) #Cloud #Data Science #Agile #Security #Data Pipeline #Redshift #Terraform #Lambda (AWS Lambda) #Data Engineering #Hadoop #Deployment #Visualization #Spark (Apache Spark) #Vulnerability Management #Databases #AWS (Amazon Web Services) #Data Architecture #SageMaker #Ansible #Leadership #Scala #Data Analysis
Role description
• Design, build, and maintain cloud-native data pipelines and analytics capabilities on an AWS-based big data platform.
• Develop and troubleshoot data engineering, integration, visualization, and ML/AI workflows using AWS services such as Glue, Lambda, Redshift, EMR, SageMaker, and QuickSight.
• Collaborate closely with data scientists to enable data analysis, visualization, and machine learning model development.
• Provide technical leadership and work cross-functionally with engineers, architects, analysts, and developers to align data architecture across projects.
• Implement DevOps and Infrastructure-as-Code practices using tools like Terraform, Ansible, or AWS CDK to support secure, scalable deployments.
• Support code quality, security, and reliability through peer reviews, vulnerability management, and occasional production support.
• Design and optimize big data and streaming solutions using technologies such as Spark, Hadoop, and relational databases, particularly Redshift.
• Operate within agile teams, partnering with product owners and engineering leaders to align business goals with technical solutions.
• Design, build, and maintain cloud-native data pipelines and analytics capabilities on an AWS-based big data platform.
• Develop and troubleshoot data engineering, integration, visualization, and ML/AI workflows using AWS services such as Glue, Lambda, Redshift, EMR, SageMaker, and QuickSight.
• Collaborate closely with data scientists to enable data analysis, visualization, and machine learning model development.
• Provide technical leadership and work cross-functionally with engineers, architects, analysts, and developers to align data architecture across projects.
• Implement DevOps and Infrastructure-as-Code practices using tools like Terraform, Ansible, or AWS CDK to support secure, scalable deployments.
• Support code quality, security, and reliability through peer reviews, vulnerability management, and occasional production support.
• Design and optimize big data and streaming solutions using technologies such as Spark, Hadoop, and relational databases, particularly Redshift.
• Operate within agile teams, partnering with product owners and engineering leaders to align business goals with technical solutions.
