Galent
Data Engineer with AI
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with AI, offering a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, Apache Spark, AWS services, SQL, and experience with large-scale data systems.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 27, 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
Columbus, OH
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🧠 - Skills detailed
#Databases #S3 (Amazon Simple Storage Service) #Python #AWS (Amazon Web Services) #"ETL (Extract #Transform #Load)" #Airflow #AI (Artificial Intelligence) #Apache Spark #Lambda (AWS Lambda) #Version Control #Kubernetes #Data Modeling #PySpark #Data Engineering #Data Processing #SQL (Structured Query Language) #Docker #GIT #Delta Lake #Spark (Apache Spark) #Redshift #Kafka (Apache Kafka) #Athena
Role description
Required Skills & Qualifications:
• Strong proficiency in Python for data processing and pipeline development
• Hands-on experience with Apache Spark (PySpark preferred)
• Solid experience with AWS services such as S3, Glue, EMR, Redshift, Athena, Lambda
• Experience with SQL and relational/non-relational databases
• Knowledge of data modeling, data warehousing concepts, and ETL frameworks
• Experience working with large-scale, distributed data systems
• Familiarity with CI/CD pipelines and version control tools (Git)
• Strong problem-solving and communication skills
Preferred / Nice to Have:
• Experience with Airflow or other workflow orchestration tools
• Knowledge of Kafka, Kinesis, or streaming data platforms
• Experience with Docker/Kubernetes
• Exposure to Delta Lake, Iceberg, or HuD.
Required Skills & Qualifications:
• Strong proficiency in Python for data processing and pipeline development
• Hands-on experience with Apache Spark (PySpark preferred)
• Solid experience with AWS services such as S3, Glue, EMR, Redshift, Athena, Lambda
• Experience with SQL and relational/non-relational databases
• Knowledge of data modeling, data warehousing concepts, and ETL frameworks
• Experience working with large-scale, distributed data systems
• Familiarity with CI/CD pipelines and version control tools (Git)
• Strong problem-solving and communication skills
Preferred / Nice to Have:
• Experience with Airflow or other workflow orchestration tools
• Knowledge of Kafka, Kinesis, or streaming data platforms
• Experience with Docker/Kubernetes
• Exposure to Delta Lake, Iceberg, or HuD.
