New York Technology Partners
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Engineer position for a contract length of "unknown" with a pay rate of "unknown," located in a "client-facing environment." Key skills include PySpark, SQL, AWS, and experience with data pipelines and MPP data warehouses.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 22, 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
Irvine, CA
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🧠 - Skills detailed
#Data Warehouse #PySpark #SQL (Structured Query Language) #Scala #Cloud #Data Modeling #Data Pipeline #Data Engineering #Kafka (Apache Kafka) #Spark SQL #Redshift #Datasets #Databricks #AWS (Amazon Web Services) #Python #Airflow #Spark (Apache Spark) #Version Control #GIT
Role description
Overview
We’re looking for a Data Engineer to build and scale modern data solutions in a client-facing environment. This role focuses on developing high-performance data pipelines, working with large datasets, and leveraging cloud and distributed technologies.
Key Responsibilities
• Design and maintain scalable data pipelines and processing frameworks
• Work with large-scale data using distributed systems
• Partner with cross-functional teams and clients to deliver data-driven solutions
• Optimize data workflows across platforms like Databricks and Kafka
• Apply best practices in data modeling, warehousing, and governance
• Support collaboration with offshore teams and global delivery efforts
Required Skills & Experience
• Strong hands-on experience with PySpark, SQL, Python, and Hive
• Cloud experience (preferably AWS)
• Experience with Airflow or similar orchestration tools
• Familiarity with version control systems (Git-based)
• Experience with MPP data warehouses (e.g., Redshift)
• Solid understanding of data warehousing concepts
• Exposure to Databricks
• Strong communication skills and client engagement experience
Overview
We’re looking for a Data Engineer to build and scale modern data solutions in a client-facing environment. This role focuses on developing high-performance data pipelines, working with large datasets, and leveraging cloud and distributed technologies.
Key Responsibilities
• Design and maintain scalable data pipelines and processing frameworks
• Work with large-scale data using distributed systems
• Partner with cross-functional teams and clients to deliver data-driven solutions
• Optimize data workflows across platforms like Databricks and Kafka
• Apply best practices in data modeling, warehousing, and governance
• Support collaboration with offshore teams and global delivery efforts
Required Skills & Experience
• Strong hands-on experience with PySpark, SQL, Python, and Hive
• Cloud experience (preferably AWS)
• Experience with Airflow or similar orchestration tools
• Familiarity with version control systems (Git-based)
• Experience with MPP data warehouses (e.g., Redshift)
• Solid understanding of data warehousing concepts
• Exposure to Databricks
• Strong communication skills and client engagement experience
