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, and experience in building APIs with FastAPI or Flask, along with data pipeline optimization and AI integration.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
520
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🗓️ - Date
June 13, 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
#Data Engineering #Data Pipeline #Spark (Apache Spark) #Flask #pydantic #Containers #Integration Testing #Data Quality #SQL (Structured Query Language) #AI (Artificial Intelligence) #Data Modeling #Batch #AWS (Amazon Web Services) #Databricks #Python #PySpark #FastAPI #Data Lifecycle #Observability
Role description
Position Summary: • We are seeking a skilled professional to build and support enterprise-grade production systems. The ideal candidate will have strong hands-on skills in PySpark, Python, and SQL, with experience in building, operating, and optimizing data pipelines. Additionally, candidates with application engineering experience should have proficiency in building APIs using FastAPI or Flask and possess robust data modeling skills. Experience integrating AI and LLMs into workflows to enhance data quality and automate processes is highly desirable. Job Must Haves: • Strong hands-on skills in PySpark, Python, and SQL • Databricks • AWS • Experience building, operating, and optimizing batch/streaming data pipelines • Experience with data quality checks and performance tuning in production • 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