

Mindlance
AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer in McLean, VA (Hybrid) for 12 months at a competitive pay rate. Requires 5–8 years of Data Engineering experience, expertise in AWS services, Python, and PySpark, and strong problem-solving skills.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
480
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🗓️ - Date
December 10, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
McLean, VA
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🧠 - Skills detailed
#Data Ingestion #Automation #Python #Data Access #S3 (Amazon Simple Storage Service) #Spark (Apache Spark) #AWS S3 (Amazon Simple Storage Service) #Data Modeling #PySpark #Compliance #Data Quality #Data Engineering #AWS Glue #Lambda (AWS Lambda) #Databricks #Data Science #Redshift #Data Lake #Athena #Scala #AWS (Amazon Web Services) #Data Governance #Data Processing #Data Pipeline #"ETL (Extract #Transform #Load)" #Security
Role description
Title: AWS Data Engineer
Location: McLean, VA (Hybrid)
Duration: 12 months
Job description:
Responsibilities:
• Design, build, and maintain scalable data pipelines using AWS Glue and Databricks.
• Develop and optimize ETL/ELT processes using PySpark and Python.
• Collaborate with data scientists, analysts, and stakeholders to enable efficient data access and transformation.
• Implement and maintain data lake and warehouse solutions on AWS (S3, Glue Catalog, Redshift, Athena, etc.).
• Ensure data quality, consistency, and reliability across systems.
• Optimize performance of large-scale distributed data processing workflows.
• Develop automation scripts and frameworks for data ingestion, transformation, and validation.
• Follow best practices for data governance, security, and compliance.
Required Skills & Experience:
• 5–8 years of hands-on experience in Data Engineering.
• Strong proficiency in Python and PySpark for data processing and transformation.
• Expertise in AWS services — particularly Glue, S3, Lambda, Redshift, and Athena.
• Hands-on experience with Databricks for building and managing data pipelines.
• Experience working with large-scale data systems and optimizing performance.
• Solid understanding of data modeling, data lake architecture, and ETL design principles.
• Strong problem-solving skills and ability to work independently in a fast-paced environment.
“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”
Title: AWS Data Engineer
Location: McLean, VA (Hybrid)
Duration: 12 months
Job description:
Responsibilities:
• Design, build, and maintain scalable data pipelines using AWS Glue and Databricks.
• Develop and optimize ETL/ELT processes using PySpark and Python.
• Collaborate with data scientists, analysts, and stakeholders to enable efficient data access and transformation.
• Implement and maintain data lake and warehouse solutions on AWS (S3, Glue Catalog, Redshift, Athena, etc.).
• Ensure data quality, consistency, and reliability across systems.
• Optimize performance of large-scale distributed data processing workflows.
• Develop automation scripts and frameworks for data ingestion, transformation, and validation.
• Follow best practices for data governance, security, and compliance.
Required Skills & Experience:
• 5–8 years of hands-on experience in Data Engineering.
• Strong proficiency in Python and PySpark for data processing and transformation.
• Expertise in AWS services — particularly Glue, S3, Lambda, Redshift, and Athena.
• Hands-on experience with Databricks for building and managing data pipelines.
• Experience working with large-scale data systems and optimizing performance.
• Solid understanding of data modeling, data lake architecture, and ETL design principles.
• Strong problem-solving skills and ability to work independently in a fast-paced environment.
“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”






