Data Architect
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Architect position based in Charlotte, NC, on a contract basis. It requires 5+ years of experience in Data Engineering, strong Python and PySpark skills, and expertise in AWS services. Key responsibilities include designing scalable ETL/ELT pipelines and optimizing data architectures.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 24, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#Programming #"ETL (Extract #Transform #Load)" #Monitoring #Delta Lake #Infrastructure as Code (IaC) #Cloud #Big Data #Terraform #Data Lake #Docker #Schema Design #Data Pipeline #Redshift #Kafka (Apache Kafka) #Python #ML (Machine Learning) #GIT #SQL (Structured Query Language) #Data Engineering #PySpark #Data Architecture #Batch #Data Science #Apache Iceberg #S3 (Amazon Simple Storage Service) #Spark (Apache Spark) #Athena #Data Modeling #Datasets #Data Warehouse #Databricks #Scala #Data Processing #Kubernetes #Data Framework #Lambda (AWS Lambda) #AWS (Amazon Web Services)
Role description
Position: Data Architect
Location: Charlotte, NC Hybrid
Employment Type: Contract
About the Role
We are seeking a skilled Data Engineer / Data Architect with strong expertise in Python, PySpark, and AWS to design, build, and optimize scalable data pipelines and cloud-based data architectures. The ideal candidate will have experience working with large-scale datasets, cloud-native services, and modern data engineering practices.
Key Responsibilities
• Design, develop, and maintain scalable ETL/ELT pipelines using Python and PySpark.
• Architect and optimize data lakes and data warehouses on AWS.
• Work with AWS services such as Glue, EMR, Redshift, S3, Lambda, Athena, Kinesis, and Step Functions.
• Ensure data reliability, quality, and governance across platforms.
• Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data solutions.
• Implement best practices for performance tuning, monitoring, and cost optimization.
• Support real-time and batch data processing frameworks.
• Provide architectural guidance and mentor junior data engineers.
Required Skills & Qualifications
• 5+ years of experience in Data Engineering or Data Architecture roles.
• Strong programming skills in Python and hands-on experience with PySpark.
• Expertise in AWS cloud ecosystem (Glue, EMR, Redshift, S3, Lambda, Athena, etc.).
• Experience with data modeling, schema design, and SQL performance optimization.
• Knowledge of data lake, data warehouse, and big data frameworks.
• Familiarity with CI/CD pipelines, Git, and Infrastructure-as-Code (IaC) tools (CloudFormation/Terraform).
• Strong understanding of ETL/ELT processes and best practices.
• Excellent problem-solving, analytical, and communication skills.
Nice to Have
• Experience with Delta Lake / Apache Iceberg / Databricks.
• Exposure to streaming frameworks (Kafka, Kinesis, Flink, Spark Streaming).
• Familiarity with containerization (Docker, Kubernetes, EKS).
• Background in machine learning pipelines or MLOps.
Position: Data Architect
Location: Charlotte, NC Hybrid
Employment Type: Contract
About the Role
We are seeking a skilled Data Engineer / Data Architect with strong expertise in Python, PySpark, and AWS to design, build, and optimize scalable data pipelines and cloud-based data architectures. The ideal candidate will have experience working with large-scale datasets, cloud-native services, and modern data engineering practices.
Key Responsibilities
• Design, develop, and maintain scalable ETL/ELT pipelines using Python and PySpark.
• Architect and optimize data lakes and data warehouses on AWS.
• Work with AWS services such as Glue, EMR, Redshift, S3, Lambda, Athena, Kinesis, and Step Functions.
• Ensure data reliability, quality, and governance across platforms.
• Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data solutions.
• Implement best practices for performance tuning, monitoring, and cost optimization.
• Support real-time and batch data processing frameworks.
• Provide architectural guidance and mentor junior data engineers.
Required Skills & Qualifications
• 5+ years of experience in Data Engineering or Data Architecture roles.
• Strong programming skills in Python and hands-on experience with PySpark.
• Expertise in AWS cloud ecosystem (Glue, EMR, Redshift, S3, Lambda, Athena, etc.).
• Experience with data modeling, schema design, and SQL performance optimization.
• Knowledge of data lake, data warehouse, and big data frameworks.
• Familiarity with CI/CD pipelines, Git, and Infrastructure-as-Code (IaC) tools (CloudFormation/Terraform).
• Strong understanding of ETL/ELT processes and best practices.
• Excellent problem-solving, analytical, and communication skills.
Nice to Have
• Experience with Delta Lake / Apache Iceberg / Databricks.
• Exposure to streaming frameworks (Kafka, Kinesis, Flink, Spark Streaming).
• Familiarity with containerization (Docker, Kubernetes, EKS).
• Background in machine learning pipelines or MLOps.
