Senior Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer with a contract length of "unknown", offering a pay rate of "unknown". Key skills include Databricks, Azure, AWS, Snowflake, Python, SQL, and Apache Spark. A Bachelor’s degree and relevant experience are required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
June 20, 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
United States
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Snowflake #Computer Science #Apache Spark #DevOps #Automation #Database Design #AWS (Amazon Web Services) #Data Engineering #GIT #ML (Machine Learning) #Python #BigQuery #Data Manipulation #Mathematics #Cloud #Data Pipeline #Data Modeling #SQL (Structured Query Language) #Big Data #Data Governance #Spark (Apache Spark) #Azure DevOps #Databricks #Data Processing #Datasets #Redshift #Security #Azure #Terraform
Role description
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Required Skills & Experience:
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
• Proven experience with Databricks for big data processing and analytics.
• Strong experience with cloud platforms, particularly Azure and AWS, and their data services.
• Hands-on experience with Snowflake, including data loading, transformation, and optimization.
• Proficiency in Python for data manipulation, pipeline development, and automation.
• Strong knowledge of SQL for querying and optimizing large datasets.
• Experience with Apache Spark for distributed data processing and optimization.
• Familiarity with ETL/ELT processes, data warehousing, and data pipeline orchestration.
• Experience with data modeling and database design to support large-scale analytics.
• Strong problem-solving skills and attention to detail.
Preferred Skills:
• Experience with other cloud-based data platforms (e.g., Google Cloud, AWS Redshift, BigQuery).
• Familiarity with DevOps practices and automation using tools like Azure DevOps, Terraform, or Git.
• Knowledge of machine learning and its integration with data pipelines is a plus.
• Experience in data governance and security practices.
