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DATA ENGINEERS WITH AWS, PYTON, PYSPARK

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with expertise in AWS, Python, and PySpark, offering a contract for $50/hr. Located in McLean, VA or Dallas, TX, candidates must have strong ETL pipeline experience and a Bachelor's degree in a related field.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
400
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πŸ—“οΈ - Date
December 28, 2025
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
W2 Contractor
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
McLean, VA
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🧠 - Skills detailed
#Data Architecture #Scala #Data Storage #Redshift #Cloud #Big Data #Computer Science #Data Integrity #Lambda (AWS Lambda) #Compliance #NumPy #Storage #PySpark #GIT #Athena #Documentation #SQL Queries #Distributed Computing #Airflow #Data Ingestion #Data Lineage #Pandas #"ETL (Extract #Transform #Load)" #Data Quality #S3 (Amazon Simple Storage Service) #DynamoDB #SQL (Structured Query Language) #Python #Snowflake #Data Processing #Programming #Spark (Apache Spark) #Data Modeling #Data Pipeline #DevOps #Security #AWS (Amazon Web Services) #Data Engineering #Apache Spark
Role description
Role: Data Engineer (AWS, Python, PySpark) Locations: McLean, VA | Dallas, TX (On-site / Face-to-Face Interview) Type: Contract Rate: $50/hr (W2) Visa Status: Open to H1T, H4-EAD, J2-EAD, L2-EAD, GC-EAD, GC, and US Citizens Job Summary We are seeking a highly skilled Data Engineer with extensive experience in AWS, Python, and PySpark to join our data engineering team. You will be responsible for designing, developing, and maintaining scalable data pipelines and architectures to support large-scale data processing and analytics. This role requires a hands-on developer who is comfortable working in a fast-paced environment and participating in in-person collaboration. Key Responsibilities Pipeline Development: Design, build, and optimize robust ETL/ELT pipelines using Python and PySpark for data ingestion, transformation, and processing. Cloud Infrastructure: Leverage AWS services (S3, Glue, EMR, Lambda, Redshift, Athena, and DynamoDB) to build and manage data storage and warehousing solutions. Data Optimization: Tune and optimize Spark jobs and SQL queries to ensure high performance and cost-efficiency in a distributed computing environment. Collaboration: Work closely with data architects and business stakeholders to translate complex requirements into technical data solutions. Quality & Governance: Implement data quality checks, validation frameworks, and security best practices to ensure data integrity and compliance. Documentation: Maintain clear technical documentation, including data lineage, schemas, and workflow processes. Required Skills & Qualifications Programming: Strong proficiency in Python (including Pandas and NumPy) and SQL. Big Data: Deep hands-on experience with Apache Spark/PySpark for large-scale distributed data processing. Cloud Ecosystem: Proven experience with AWS data services (specifically Glue, EMR, and Redshift). Data Modeling: Solid understanding of data warehousing concepts, including Star and Snowflake schemas. DevOps/Tools: Familiarity with Git, CI/CD pipelines, and workflow orchestration tools (e.g., Airflow or Step Functions). Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Submission Requirements Visa Status: Open to H1T, H4-EAD, J2-EAD, L2-EAD, GC-EAD, GC, and US Citizens. Interview Mode: Must be available for a Face-to-Face (F2F) interview at the specified location. Work Arrangement: Candidates must be willing to work on-site in McLean, VA or Dallas, TX. Job Type: Contract Pay: $45.00 - $50.00 per hour Expected hours: 9 per week Work Location: On the road