New York Technology Partners
Data Engineer (PySpark)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (PySpark) with a contract length of "unknown," offering a pay rate of "unknown," and requiring expertise in PySpark, Python, SQL, and cloud platforms. Familiarity with Databricks and experience in client-facing roles are essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 29, 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
#Databricks #Version Control #SQL (Structured Query Language) #"ETL (Extract #Transform #Load)" #PySpark #Data Pipeline #Datasets #GIT #Scala #Kafka (Apache Kafka) #Data Engineering #Data Warehouse #Data Modeling #Spark (Apache Spark) #Python #Redshift #BitBucket #GitHub #Airflow #AWS (Amazon Web Services) #Cloud
Role description
We are looking for a Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions in a cloud-based environment. The role involves working with large-scale data systems, modern data platforms, and collaborating closely with business stakeholders and engineering teams in a client-facing setting.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines and ETL processes
• Work with large datasets using distributed processing frameworks like PySpark
• Build and optimize data solutions on platforms such as Databricks and Kafka
• Implement data models, warehousing solutions, and governance best practices
• Collaborate with cross-functional teams and client stakeholders to deliver solutions
• Support offshore teams and contribute to global delivery execution
Required Skills:
• Strong hands-on experience in PySpark, Python, SQL, and Hive
• Cloud experience (preferably AWS)
• Experience with Databricks and workflow orchestration tools like Airflow
• Familiarity with MPP data warehouses (e.g., Redshift or similar)
• Solid understanding of data warehousing and data modeling concepts
• Proficiency with Git-based version control (GitHub/Bitbucket)
• Strong communication and client-facing experience
• Experience working in distributed/offshore team environments
We are looking for a Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions in a cloud-based environment. The role involves working with large-scale data systems, modern data platforms, and collaborating closely with business stakeholders and engineering teams in a client-facing setting.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines and ETL processes
• Work with large datasets using distributed processing frameworks like PySpark
• Build and optimize data solutions on platforms such as Databricks and Kafka
• Implement data models, warehousing solutions, and governance best practices
• Collaborate with cross-functional teams and client stakeholders to deliver solutions
• Support offshore teams and contribute to global delivery execution
Required Skills:
• Strong hands-on experience in PySpark, Python, SQL, and Hive
• Cloud experience (preferably AWS)
• Experience with Databricks and workflow orchestration tools like Airflow
• Familiarity with MPP data warehouses (e.g., Redshift or similar)
• Solid understanding of data warehousing and data modeling concepts
• Proficiency with Git-based version control (GitHub/Bitbucket)
• Strong communication and client-facing experience
• Experience working in distributed/offshore team environments
