Tenth Revolution Group
AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer, contract duration of at least 6 months, fully remote. Requires senior-level experience in data engineering, AWS platforms, data modeling, Python, and SQL. Financial services industry experience is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
January 17, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#API (Application Programming Interface) #Python #SQL (Structured Query Language) #Version Control #Data Dictionary #AWS (Amazon Web Services) #Lambda (AWS Lambda) #Data Modeling #Snowflake #Data Integrity #Consulting #Monitoring #Data Quality #Code Reviews #DMS (Data Migration Service) #Terraform #"ETL (Extract #Transform #Load)" #Aurora PostgreSQL #Documentation #DevOps #AWS Glue #Aurora #Data Pipeline #PostgreSQL #SQL Queries #GitHub #Data Engineering
Role description
Location: Fully Remote (US)
Duration: Minimum 6 months
Start: 2/9 onwards
Engagement: Contract
Industry: Financial Services
We are supporting a premium AWS consulting partner that is currently working through a pressing customer engagement within financial services. They are looking to engage a senior-level Data Engineer with strong enterprise data exposure to help stabilize, optimize, and extend a production-grade AWS data platform.
This is a hands-on role focused on data modeling, event-driven pipelines, and enterprise data assets, working closely with engineering and platform teams.
Key Responsibilities:
Data Modeling
• Maintain, extend, and optimize data models in Aurora PostgreSQL and Snowflake
• Modify logical and physical schemas to support new requirements and performance improvements
• Ensure strong data integrity and maintain documentation within the enterprise data dictionary
Enterprise Data & API Development
• Contribute to shared enterprise-wide data assets
• Write and optimize complex SQL queries supporting internal and external APIs
• Partner with application and platform teams to enable reliable downstream consumption
Data Pipeline Engineering
• Maintain and enhance event-driven data pipelines using AWS Glue, Lambda, DMS, and Python
• Refactor ETL logic, tune performance, and deliver new features
• Work with AWS EventBridge workflows
• Implement data quality checks, monitoring, and alerting
System Integration & DevOps
• Contribute to and maintain CI/CD pipelines using GitHub Actions
• Follow strong version control practices, including code reviews via GitHub
• Collaborate on infrastructure topics, including Terraform and artifact management
• Troubleshoot and resolve production data pipeline issues
Required Experience
• Senior-level Data Engineering background with strong enterprise data exposure
• Deep experience building and supporting AWS-based data platforms
• Strong data modeling skills across transactional and analytical systems
• Hands-on experience with Snowflake and PostgreSQL
• Event-driven architecture experience using AWS native services
• Strong Python and SQL skills
• Comfortable operating in fast-moving, client-facing consulting environments
Nice to Have
• Prior experience in financial services
• Exposure to regulated or highly governed data environments
• Experience supporting API-driven data products
Location: Fully Remote (US)
Duration: Minimum 6 months
Start: 2/9 onwards
Engagement: Contract
Industry: Financial Services
We are supporting a premium AWS consulting partner that is currently working through a pressing customer engagement within financial services. They are looking to engage a senior-level Data Engineer with strong enterprise data exposure to help stabilize, optimize, and extend a production-grade AWS data platform.
This is a hands-on role focused on data modeling, event-driven pipelines, and enterprise data assets, working closely with engineering and platform teams.
Key Responsibilities:
Data Modeling
• Maintain, extend, and optimize data models in Aurora PostgreSQL and Snowflake
• Modify logical and physical schemas to support new requirements and performance improvements
• Ensure strong data integrity and maintain documentation within the enterprise data dictionary
Enterprise Data & API Development
• Contribute to shared enterprise-wide data assets
• Write and optimize complex SQL queries supporting internal and external APIs
• Partner with application and platform teams to enable reliable downstream consumption
Data Pipeline Engineering
• Maintain and enhance event-driven data pipelines using AWS Glue, Lambda, DMS, and Python
• Refactor ETL logic, tune performance, and deliver new features
• Work with AWS EventBridge workflows
• Implement data quality checks, monitoring, and alerting
System Integration & DevOps
• Contribute to and maintain CI/CD pipelines using GitHub Actions
• Follow strong version control practices, including code reviews via GitHub
• Collaborate on infrastructure topics, including Terraform and artifact management
• Troubleshoot and resolve production data pipeline issues
Required Experience
• Senior-level Data Engineering background with strong enterprise data exposure
• Deep experience building and supporting AWS-based data platforms
• Strong data modeling skills across transactional and analytical systems
• Hands-on experience with Snowflake and PostgreSQL
• Event-driven architecture experience using AWS native services
• Strong Python and SQL skills
• Comfortable operating in fast-moving, client-facing consulting environments
Nice to Have
• Prior experience in financial services
• Exposure to regulated or highly governed data environments
• Experience supporting API-driven data products
