Optomi
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with a contract length of "unknown," offering a pay rate of "unknown," and is remote. Key skills include PySpark, Python, SQL, AWS services, API development, and strong data modeling. Experience with AI integration is highly desirable.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
August 19, 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
Jersey City, NJ
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🧠 - Skills detailed
#Batch #Containers #Flask #Data Engineering #Data Modeling #IAM (Identity and Access Management) #Python #FastAPI #Databricks #AWS (Amazon Web Services) #Observability #Data Quality #pydantic #SQL (Structured Query Language) #Spark (Apache Spark) #PySpark #AI (Artificial Intelligence) #Data Lifecycle #Lambda (AWS Lambda) #Integration Testing #Data Pipeline #S3 (Amazon Simple Storage Service)
Role description
Summary: We are seeking an experienced professional to design, build, and support enterprise-grade production systems. The ideal candidate will bring strong hands-on expertise in PySpark, Python, and SQL, along with a proven ability to develop, operate, and optimize data pipelines. Candidates with application engineering experience should also be proficient in building APIs with FastAPI or Flask and possess strong data modeling capabilities. Experience integrating AI and large language models into workflows to improve data quality and automate processes is highly desirable.
Job Must Haves:
• Expert in PySpark (with Databricks), Python, and SQL
• AWS Services (S3, Glue, Lambda, Step Functions, IAM)
• Experience building APIs and backend services using FastAPI or Flask
• Strong data modeling skills (e.g., Pydantic)
• Experience with event-driven architectures, concurrency/async processing, database integration, testing, CI/CD, containers, and production observability
Job Nice to Haves:
• Practical experience integrating AI and Large Language Models (LLMs) into data platforms and workflows
• Leveraging AI technologies to enhance data quality and observability
• Automating repetitive processes
• Delivering smarter, faster outcomes across the data lifecycle
What the responsibilities are of the right candidate:
• Build and support enterprise-grade production systems
• Optimize batch/streaming data pipelines
• Integrate AI and LLMs into data platforms
• Enhance data quality and automate processes
Summary: We are seeking an experienced professional to design, build, and support enterprise-grade production systems. The ideal candidate will bring strong hands-on expertise in PySpark, Python, and SQL, along with a proven ability to develop, operate, and optimize data pipelines. Candidates with application engineering experience should also be proficient in building APIs with FastAPI or Flask and possess strong data modeling capabilities. Experience integrating AI and large language models into workflows to improve data quality and automate processes is highly desirable.
Job Must Haves:
• Expert in PySpark (with Databricks), Python, and SQL
• AWS Services (S3, Glue, Lambda, Step Functions, IAM)
• Experience building APIs and backend services using FastAPI or Flask
• Strong data modeling skills (e.g., Pydantic)
• Experience with event-driven architectures, concurrency/async processing, database integration, testing, CI/CD, containers, and production observability
Job Nice to Haves:
• Practical experience integrating AI and Large Language Models (LLMs) into data platforms and workflows
• Leveraging AI technologies to enhance data quality and observability
• Automating repetitive processes
• Delivering smarter, faster outcomes across the data lifecycle
What the responsibilities are of the right candidate:
• Build and support enterprise-grade production systems
• Optimize batch/streaming data pipelines
• Integrate AI and LLMs into data platforms
• Enhance data quality and automate processes
