Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with 8+ years of experience, focusing on AWS deployment, SQL, Python, and CI/CD pipelines. Requires Fannie Mae knowledge, experience with APIs, and tools like Spark and Power BI. Contract length and pay rate unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
-
🗓️ - Date discovered
September 11, 2025
🕒 - Project duration
Unknown
-
🏝️ - Location type
Unknown
-
📄 - Contract type
Unknown
-
🔒 - Security clearance
Unknown
-
📍 - Location detailed
Reston, VA
-
🧠 - Skills detailed
#Data Modeling #Python #AWS EMR (Amazon Elastic MapReduce) #S3 (Amazon Simple Storage Service) #Cloud #SNS (Simple Notification Service) #RDS (Amazon Relational Database Service) #Airflow #AWS Glue #Lambda (AWS Lambda) #Data Engineering #BI (Business Intelligence) #Spark (Apache Spark) #GitLab #Microsoft Power BI #SQS (Simple Queue Service) #SQL (Structured Query Language) #Data Analysis #AWS (Amazon Web Services) #Redshift
Role description
8+ years of Data Engineering experience
Data Engineering and insight experience.
Experience in building and deploying applications in AWS using services like (S3, Glue, Redshift, RDS, AWS EMR, CloudWatch, Lambda, State Machine, SNS, SQS, ECS, AppFlow, etc.).
SQL and Data Analysis.
Exp with APIs, RESTful services.
Strong Python experience. Strong exp building CI/CD pipelines on AWS (CloudFormation and Gitlab). Fannie Mae Institutional knowledge.strong SQL, data modeling, and tools like Spark / Hive / Airflow. Professional certification(s) desired, 5-10 years relevant experience.
Skilled in leveraging S3, Redshift, AWS Glue, EMR, and Power BI to deliver secure, high-performance solutions and self-service BI ecosystems.
#LI-CGTS
#TS-0942
8+ years of Data Engineering experience
Data Engineering and insight experience.
Experience in building and deploying applications in AWS using services like (S3, Glue, Redshift, RDS, AWS EMR, CloudWatch, Lambda, State Machine, SNS, SQS, ECS, AppFlow, etc.).
SQL and Data Analysis.
Exp with APIs, RESTful services.
Strong Python experience. Strong exp building CI/CD pipelines on AWS (CloudFormation and Gitlab). Fannie Mae Institutional knowledge.strong SQL, data modeling, and tools like Spark / Hive / Airflow. Professional certification(s) desired, 5-10 years relevant experience.
Skilled in leveraging S3, Redshift, AWS Glue, EMR, and Power BI to deliver secure, high-performance solutions and self-service BI ecosystems.
#LI-CGTS
#TS-0942
