Redolent, Inc
Senior Data Engineer | (Big Data & MLOps) | W2 | Onsite
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer (Big Data & MLOps) based in Pittsburgh, PA, with a contract length of W2. Requires 5+ years of experience, proficiency in Python, PySpark, SQL, and container technologies like OpenShift and Kubernetes.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 7, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Pittsburgh, PA
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🧠 - Skills detailed
#Big Data #Scala #Spark (Apache Spark) #SQL (Structured Query Language) #DataOps #ML (Machine Learning) #Deployment #Data Quality #Data Science #Unix #Apache Spark #Linux #PySpark #Data Engineering #Security #Python #Automation #Spark SQL #Model Deployment #"ETL (Extract #Transform #Load)" #Computer Science #Kubernetes #Data Processing
Role description
Position: Senior Data Engineer | (Big Data & MLOps) | W2 | Onsite
Location: Onsite 5 days a week Pittsburgh, PA
Develop scalable ETL/ELT solutions using Python, PySpark, Spark, SQL, and Hive
• .Deploy and manage applications in OpenShift/Kubernetes container environments
• .Collaborate with Data Scientists, ML Engineers, and cross-functional teams to operationalize machine learning models
• .Optimize Big Data processing frameworks and improve data platform performance
• .Troubleshoot and resolve issues in Linux/Unix environments
• .Implement best practices for DataOps and MLOps, including CI/CD for data and ML workflows
• .Ensure data quality, reliability, scalability, and security across data platforms
.Required Qualifications
• :Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field
• .5+ years of experience as a Data Engineer, Senior Data Engineer, Big Data Engineer, MLOps Engineer, or related role
• .Hands-on experience building Machine Learning pipelines and supporting model deployment and training processes
• .Strong experience with OpenShift, Kubernetes, and container technologies
• .Proficiency in Python and/or PySpark for data engineering and automation tasks
• .Strong experience with SQL, Hive, Spark, and Apache Spark
• .Experience working in Linux/Unix environments
• .Knowledge of DataOps and MLOps methodologies and best practices
.
Position: Senior Data Engineer | (Big Data & MLOps) | W2 | Onsite
Location: Onsite 5 days a week Pittsburgh, PA
Develop scalable ETL/ELT solutions using Python, PySpark, Spark, SQL, and Hive
• .Deploy and manage applications in OpenShift/Kubernetes container environments
• .Collaborate with Data Scientists, ML Engineers, and cross-functional teams to operationalize machine learning models
• .Optimize Big Data processing frameworks and improve data platform performance
• .Troubleshoot and resolve issues in Linux/Unix environments
• .Implement best practices for DataOps and MLOps, including CI/CD for data and ML workflows
• .Ensure data quality, reliability, scalability, and security across data platforms
.Required Qualifications
• :Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field
• .5+ years of experience as a Data Engineer, Senior Data Engineer, Big Data Engineer, MLOps Engineer, or related role
• .Hands-on experience building Machine Learning pipelines and supporting model deployment and training processes
• .Strong experience with OpenShift, Kubernetes, and container technologies
• .Proficiency in Python and/or PySpark for data engineering and automation tasks
• .Strong experience with SQL, Hive, Spark, and Apache Spark
• .Experience working in Linux/Unix environments
• .Knowledge of DataOps and MLOps methodologies and best practices
.
