PineQ Lab Technology
AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer with strong expertise in AWS services like Redshift, EMR, and Glue. Requires experience in ETL/ELT pipelines, data warehousing, SQL, Python, and data lake architectures. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 8, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Malvern, PA
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🧠 - Skills detailed
#Data Lake #Schema Design #Hadoop #Data Modeling #Amazon Redshift #Data Processing #Lambda (AWS Lambda) #S3 (Amazon Simple Storage Service) #Data Engineering #Spark (Apache Spark) #AWS Glue #AWS (Amazon Web Services) #Redshift #Amazon EMR (Amazon Elastic MapReduce) #"ETL (Extract #Transform #Load)" #PySpark #Programming #HDFS (Hadoop Distributed File System) #Cloud #IAM (Identity and Access Management) #Python #SQL (Structured Query Language)
Role description
Strong experience in AWS Data Engineering services: Redshift, EMR, AWS Glue, S3, IAM, Lambda, CloudWatch.
• Expertise in designing and developing ETL/ELT pipelines using AWS Glue and PySpark.
• Hands-on experience with Amazon Redshift for data warehousing, performance tuning, schema design, and query optimization.
• Proficiency in Amazon EMR for large-scale data processing using Hadoop, Spark, Hive, and HDFS.
• Strong SQL and Python programming skills for data transformation and analytics.
• Experience with data lake architectures, data modeling, and handling structured/semi-structured data.
Strong experience in AWS Data Engineering services: Redshift, EMR, AWS Glue, S3, IAM, Lambda, CloudWatch.
• Expertise in designing and developing ETL/ELT pipelines using AWS Glue and PySpark.
• Hands-on experience with Amazon Redshift for data warehousing, performance tuning, schema design, and query optimization.
• Proficiency in Amazon EMR for large-scale data processing using Hadoop, Spark, Hive, and HDFS.
• Strong SQL and Python programming skills for data transformation and analytics.
• Experience with data lake architectures, data modeling, and handling structured/semi-structured data.
