TriOptus
Big Data Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Big Data Developer with 8+ years of experience, focusing on distributed systems and data pipelines. Requires expertise in PySpark, Kafka, and cloud platforms. A degree in Computer Science or related field is essential. Remote position.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
October 2, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
San Antonio, Texas Metropolitan Area
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🧠 - Skills detailed
#AI (Artificial Intelligence) #AWS (Amazon Web Services) #Compliance #Deployment #GCP (Google Cloud Platform) #Big Data #Scala #Spark (Apache Spark) #PySpark #Data Pipeline #Azure #Cloud #Kafka (Apache Kafka) #Mathematics #Computer Science #ML (Machine Learning)
Role description
Big Data Developer
Remote
8+ years of experience across the full software development lifecycle (design, coding, reviews, testing, deployment, operations)
• 5+ years of experience with distributed Big Data systems (e.g., PySpark, Lakehouse, Kafka, Debezium, Hudi, Druid, Flink, Spark Streaming)
Lead the design and development of distributed systems, data pipelines, and ML infrastructure with a focus on scalability and reliability
Own end-to-end delivery of key features and services across the full SDLC design, implementation, testing, deployment, and operations
Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready systems
Build and optimize scalable, real-time analytic systems powering AI Agents
Mentor junior and mid-level engineers, provide technical guidance, and promote engineering best practices
Collaborate across teams to ensure solutions are resilient, secure, and high-performing Requirements
Degree in Computer Science, Mathematics, or a related field
Experience with sensitive or streaming data pipelines, including governance and compliance requirements
Experience with Graph technologies (e.g., GNNs)
Proven track record of delivering complex, high-impact software systems in production
Experience deploying large-scale solutions on cloud platforms (AWS, Azure, GCP)Strong problem-solving skills and ability to excel in ambiguous environments
Preferred Qualifications: MS in Computer Science, Machine Learning, or a related discipline
Experience with Graph ML and Graph technologies (e.g., GNNs)
Hands-on experience building Generative AI solutions (RAG, AI Agents, LLM fine-tuning) in production
Big Data Developer
Remote
8+ years of experience across the full software development lifecycle (design, coding, reviews, testing, deployment, operations)
• 5+ years of experience with distributed Big Data systems (e.g., PySpark, Lakehouse, Kafka, Debezium, Hudi, Druid, Flink, Spark Streaming)
Lead the design and development of distributed systems, data pipelines, and ML infrastructure with a focus on scalability and reliability
Own end-to-end delivery of key features and services across the full SDLC design, implementation, testing, deployment, and operations
Drive innovation in Big Data, Generative AI, and Graph ML by translating emerging technologies into production-ready systems
Build and optimize scalable, real-time analytic systems powering AI Agents
Mentor junior and mid-level engineers, provide technical guidance, and promote engineering best practices
Collaborate across teams to ensure solutions are resilient, secure, and high-performing Requirements
Degree in Computer Science, Mathematics, or a related field
Experience with sensitive or streaming data pipelines, including governance and compliance requirements
Experience with Graph technologies (e.g., GNNs)
Proven track record of delivering complex, high-impact software systems in production
Experience deploying large-scale solutions on cloud platforms (AWS, Azure, GCP)Strong problem-solving skills and ability to excel in ambiguous environments
Preferred Qualifications: MS in Computer Science, Machine Learning, or a related discipline
Experience with Graph ML and Graph technologies (e.g., GNNs)
Hands-on experience building Generative AI solutions (RAG, AI Agents, LLM fine-tuning) in production
