Quantum World Technologies Inc.
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer in St. Louis, MO, with a contract length of "unknown". The pay rate is "unknown". Requires 8+ years of data engineering experience, 3+ years leading teams, expertise in PySpark, Databricks, AWS, and building enterprise-scale data solutions.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 24, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Spark (Apache Spark) #Data Pipeline #Databricks #Data Engineering #Data Ingestion #"ETL (Extract #Transform #Load)" #Scala #CLI (Command-Line Interface) #AWS (Amazon Web Services) #Cloud #Storage #AI (Artificial Intelligence) #GitHub #AWS EMR (Amazon Elastic MapReduce) #PySpark
Role description
Role- Lead - Data / AI Native Engineer
Location - St. Louis MO (Onsite)
Preferred Qualification –
• 8+ years of Data Engineering and Software Engineering experience.
• 3+ years leading complex data engineering initiatives or engineering teams.
• Proven experience building enterprise-scale data platforms and pipelines.
• Experience delivering cloud-native analytics and AI solutions. Build highly available, secure, and scalable cloud-native data solutions.
• Develop ETL/ELT frameworks for ingesting, transforming, and publishing enterprise data.
• Implement high-volume distributed processing using Spark and PySpark.
• Leverage GitHub Copilot, Claude Code CLI, and AI-assisted development tools to accelerate engineering productivity.
Technical Skills
• Primary skills :- Pyspark n Databricks along with Data / AI Native Engineer skills
• Build Proof of Concepts (POCs) and MVPs using AI-powered development approaches.
• Develop cloud-native solutions leveraging AWS and Databricks ecosystems.
• Build scalable architectures for data ingestion, processing, storage, and analytics.
Key Expectations
• Strong experience in building enterprise-grade data pipelines, modern Lakehouse architectures, AI-enabled data products, and cloud-native platforms leveraging Databricks, AWS EMR, Spark, PySpark, and AI-native engineering tools such as GitHub Copilot and Claude Code.
Role- Lead - Data / AI Native Engineer
Location - St. Louis MO (Onsite)
Preferred Qualification –
• 8+ years of Data Engineering and Software Engineering experience.
• 3+ years leading complex data engineering initiatives or engineering teams.
• Proven experience building enterprise-scale data platforms and pipelines.
• Experience delivering cloud-native analytics and AI solutions. Build highly available, secure, and scalable cloud-native data solutions.
• Develop ETL/ELT frameworks for ingesting, transforming, and publishing enterprise data.
• Implement high-volume distributed processing using Spark and PySpark.
• Leverage GitHub Copilot, Claude Code CLI, and AI-assisted development tools to accelerate engineering productivity.
Technical Skills
• Primary skills :- Pyspark n Databricks along with Data / AI Native Engineer skills
• Build Proof of Concepts (POCs) and MVPs using AI-powered development approaches.
• Develop cloud-native solutions leveraging AWS and Databricks ecosystems.
• Build scalable architectures for data ingestion, processing, storage, and analytics.
Key Expectations
• Strong experience in building enterprise-grade data pipelines, modern Lakehouse architectures, AI-enabled data products, and cloud-native platforms leveraging Databricks, AWS EMR, Spark, PySpark, and AI-native engineering tools such as GitHub Copilot and Claude Code.
