[Remote] Senior Data Engineer (AI) -- Pittsburgh, PA/ Remote /W2/

Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Senior Data Engineer (AI) to join their team, offering a contract position through the end of 2026. The role involves building and maintaining enterprise-scale data pipelines, leveraging Azure data services and Databricks for data processing and integration.

Responsibilities

• Strong hands-on experience with Azure data services, including: Azure Data Lake Storage (ADLS), Azure Data Factory and/or Synapse Pipelines
• Deep experience with Databricks, including Spark / PySpark development and performance optimization
• Proven experience building and maintaining enterprise-scale data pipelines
• Experience integrating data from diverse enterprise systems (databases, APIs, cloud platforms)
• Solid understanding of data architecture principles, data modeling, and ETL/ELT patterns
• Experience with pipeline orchestration, automation, and monitoring
• Working knowledge of MLOps concepts, including supporting data workflows for model training and deployment
• Strong troubleshooting and performance tuning skills in distributed environments
• Familiarity with data governance, security, and access control frameworks
• Proficiency in Python and SQL
• Strong collaboration and communication skills

Skills

• 7+ years of professional experience (post-graduate) in data engineering or related field
• Strong hands-on experience with Azure data services, including: Azure Data Lake Storage (ADLS), Azure Data Factory and/or Synapse Pipelines
• Deep experience with Databricks, including Spark / PySpark development and performance optimization
• Proven experience building and maintaining enterprise-scale data pipelines
• Experience integrating data from diverse enterprise systems (databases, APIs, cloud platforms)
• Solid understanding of data architecture principles, data modeling, and ETL/ELT patterns
• Experience with pipeline orchestration, automation, and monitoring
• Working knowledge of MLOps concepts, including supporting data workflows for model training and deployment
• Strong troubleshooting and performance tuning skills in distributed environments
• Familiarity with data governance, security, and access control frameworks
• Proficiency in Python and SQL
• Strong collaboration and communication skills

Company Overview

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