Intellectt Inc
Lead Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Engineer, offering a contract length of "unknown" with a pay rate of "unknown," located on-site in NJ. Key skills include AWS, Python, PySpark, SQL, and experience with big data technologies.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
440
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🗓️ - Date
April 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
Berkeley Heights, NJ
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🧠 - Skills detailed
#Big Data #Data Pipeline #Data Quality #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Data Engineering #Data Modeling #Data Lake #Redshift #PySpark #"ETL (Extract #Transform #Load)" #Snowflake #Terraform #AWS S3 (Amazon Simple Storage Service) #Athena #Lambda (AWS Lambda) #Scala #SQL (Structured Query Language) #Infrastructure as Code (IaC) #ML (Machine Learning) #Spark SQL #S3 (Amazon Simple Storage Service) #Apache Spark #Visualization #BI (Business Intelligence) #Python #Security #TensorFlow #Hadoop #Cloud #Batch #Data Science #Microsoft Power BI #Spark (Apache Spark) #Data Warehouse #SageMaker
Role description
Number of Positions: 1 Lead and 1 Senior (Both Required).
Interview Mode: L1 & In-person in NJ.
Key Skills Required:
• AWS (S3, Redshift, Glue, Lambda, EMR, Athena).
• Data Engineering & Data Modeling (Star Schema, Snowflake, Dimensional Modeling).
• Python, PySpark, SQL.
• Big Data Technologies (Hadoop, Spark).
• Infrastructure as Code (Terraform).
• AI/ML integration basics.
• Visualization tools (Power BI).
Roles & Responsibilities:
• Design, develop, and maintain scalable data pipelines for batch and real-time processing using AWS services
• Build and optimize data lakes and data warehouses using Amazon S3, Redshift, and Glue
• Develop robust ETL/ELT pipelines using Python, PySpark, and SQL
• Implement efficient data modeling techniques such as star schema and dimensional modeling
• Work with large-scale distributed systems using Hadoop and Apache Spark
• Integrate AI/ML models into data pipelines to support advanced analytics
• Automate infrastructure provisioning using Terraform (IaC)
• Ensure data quality, governance, and security across pipelines
• Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders
• Develop dashboards and reports using Power BI for business insights
• Monitor and optimize performance of data pipelines and cloud resources.
• Exposure to AI/ML frameworks (SageMaker, TensorFlow, etc.)
Number of Positions: 1 Lead and 1 Senior (Both Required).
Interview Mode: L1 & In-person in NJ.
Key Skills Required:
• AWS (S3, Redshift, Glue, Lambda, EMR, Athena).
• Data Engineering & Data Modeling (Star Schema, Snowflake, Dimensional Modeling).
• Python, PySpark, SQL.
• Big Data Technologies (Hadoop, Spark).
• Infrastructure as Code (Terraform).
• AI/ML integration basics.
• Visualization tools (Power BI).
Roles & Responsibilities:
• Design, develop, and maintain scalable data pipelines for batch and real-time processing using AWS services
• Build and optimize data lakes and data warehouses using Amazon S3, Redshift, and Glue
• Develop robust ETL/ELT pipelines using Python, PySpark, and SQL
• Implement efficient data modeling techniques such as star schema and dimensional modeling
• Work with large-scale distributed systems using Hadoop and Apache Spark
• Integrate AI/ML models into data pipelines to support advanced analytics
• Automate infrastructure provisioning using Terraform (IaC)
• Ensure data quality, governance, and security across pipelines
• Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders
• Develop dashboards and reports using Power BI for business insights
• Monitor and optimize performance of data pipelines and cloud resources.
• Exposure to AI/ML frameworks (SageMaker, TensorFlow, etc.)
