Prestige Staffing
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer on a 4-6 month contract, 100% remote. Requires 2+ years of experience, strong Python and SQL skills, and expertise in cloud platforms (Azure, AWS, GCP). Familiarity with ETL/ELT pipelines and operational datasets is essential.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
400
-
🗓️ - Date
May 21, 2026
🕒 - Duration
3 to 6 months
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Charlotte, NC
-
🧠 - Skills detailed
#Model Deployment #Cloud #"ETL (Extract #Transform #Load)" #AWS (Amazon Web Services) #GCP (Google Cloud Platform) #Data Science #Storage #Data Lake #Data Quality #Data Pipeline #AI (Artificial Intelligence) #Observability #Datasets #Python #Deployment #Azure #Data Engineering #SQL (Structured Query Language) #Data Processing #Scala #Batch #Monitoring #Databases #ML (Machine Learning)
Role description
Location: 100% Remote (Candidates in Eastern or Central Time Zones Preferred)
Function: Engineering
Type: 4-6 month contract
Role Overview
Seeking a hands-on Data Engineer to design, build, and maintain the data infrastructure and pipelines that power a suite of operational, analytics, and AI-driven solutions.
This role focuses on continuously ingesting, processing, and organizing large volumes of customer and operational data from diverse systems, applications, and devices. You will be responsible for building scalable data pipelines, cloud-based infrastructure, and real-time data flows that support analytics, machine learning models, and production applications.
This is a highly technical, builder-focused role for someone who enjoys working close to the data, solving real-world engineering challenges, and enabling downstream teams through reliable and well-structured data systems.
What You Will Do
• Design and build scalable data pipelines for ingestion of operational and customer data
• Develop both batch and real-time data processing workflows
• Integrate data from APIs, databases, third-party platforms, and event-driven systems
• Build and maintain cloud-based data infrastructure and storage solutions
• Ensure data quality, reliability, monitoring, and observability across pipelines
• Support analytics, AI, and application teams with clean, well-structured datasets
• Optimize pipelines for performance, scalability, and cost efficiency
• Collaborate closely with engineering, product, and operations teams on evolving requirements
What Success Looks Like
• 2+ years of experience in data engineering or related roles
• Strong experience building ETL/ELT pipelines and working with distributed data systems
• Hands-on experience with cloud platforms (Azure, AWS, or GCP)
• Strong proficiency in Python and SQL
• Experience with APIs, streaming data, or event-driven architectures
• Familiarity with modern data stacks (data lakes, warehouses, orchestration tools)
• Experience working with complex, operational datasets is a strong plus
• Comfortable working in fast-paced, evolving environments with limited structure
Nice to Have
• Exposure to machine learning or AI model deployment workflows
• Experience with advanced Python-based data science or ML tooling
• Familiarity with computer vision or sensor-based data environments
• Experience owning end-to-end data or ML pipelines in production
Location: 100% Remote (Candidates in Eastern or Central Time Zones Preferred)
Function: Engineering
Type: 4-6 month contract
Role Overview
Seeking a hands-on Data Engineer to design, build, and maintain the data infrastructure and pipelines that power a suite of operational, analytics, and AI-driven solutions.
This role focuses on continuously ingesting, processing, and organizing large volumes of customer and operational data from diverse systems, applications, and devices. You will be responsible for building scalable data pipelines, cloud-based infrastructure, and real-time data flows that support analytics, machine learning models, and production applications.
This is a highly technical, builder-focused role for someone who enjoys working close to the data, solving real-world engineering challenges, and enabling downstream teams through reliable and well-structured data systems.
What You Will Do
• Design and build scalable data pipelines for ingestion of operational and customer data
• Develop both batch and real-time data processing workflows
• Integrate data from APIs, databases, third-party platforms, and event-driven systems
• Build and maintain cloud-based data infrastructure and storage solutions
• Ensure data quality, reliability, monitoring, and observability across pipelines
• Support analytics, AI, and application teams with clean, well-structured datasets
• Optimize pipelines for performance, scalability, and cost efficiency
• Collaborate closely with engineering, product, and operations teams on evolving requirements
What Success Looks Like
• 2+ years of experience in data engineering or related roles
• Strong experience building ETL/ELT pipelines and working with distributed data systems
• Hands-on experience with cloud platforms (Azure, AWS, or GCP)
• Strong proficiency in Python and SQL
• Experience with APIs, streaming data, or event-driven architectures
• Familiarity with modern data stacks (data lakes, warehouses, orchestration tools)
• Experience working with complex, operational datasets is a strong plus
• Comfortable working in fast-paced, evolving environments with limited structure
Nice to Have
• Exposure to machine learning or AI model deployment workflows
• Experience with advanced Python-based data science or ML tooling
• Familiarity with computer vision or sensor-based data environments
• Experience owning end-to-end data or ML pipelines in production
