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 and Azure. Contract length is unspecified, with a competitive pay rate. Key skills include ETL, data governance, and proficiency in Apache Spark, Airflow, and Power BI.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
May 21, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Reston, VA
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🧠 - Skills detailed
#Microsoft Power BI #PySpark #AWS (Amazon Web Services) #Azure #Cloud #Data Engineering #Data Integration #AWS Glue #"ETL (Extract #Transform #Load)" #Apache Spark #Redshift #Spark (Apache Spark) #Scala #BI (Business Intelligence) #Data Governance #S3 (Amazon Simple Storage Service) #Apache Airflow #Data Lake #Airflow
Role description
8+ years of Data Engineering experience
5+ years of experience in designing scalable, cloud-native platforms using AWS, Azure,
Skilled in leveraging S3, Redshift, AWS Glue, EMR, Azure Data Lake, and Power BI to deliver secure, high-performance solutions and self-service BI ecosystems.
Proven ability to optimize data integration pipelines (ETL/ELT), implementing Change Data Capture (CDC) for Analytics projects, and drive robust data governance.
Skilled in leveraging Apache Airflow, Apache Flink and other Data tools
Experienced in distributed data compute architecture using Apache Spark and PySpark.
8+ years of Data Engineering experience
5+ years of experience in designing scalable, cloud-native platforms using AWS, Azure,
Skilled in leveraging S3, Redshift, AWS Glue, EMR, Azure Data Lake, and Power BI to deliver secure, high-performance solutions and self-service BI ecosystems.
Proven ability to optimize data integration pipelines (ETL/ELT), implementing Change Data Capture (CDC) for Analytics projects, and drive robust data governance.
Skilled in leveraging Apache Airflow, Apache Flink and other Data tools
Experienced in distributed data compute architecture using Apache Spark and PySpark.
