CloudIngest

Data Engineer Lead with Gen AI (Only W2) (Expect H1B))

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer Lead with Gen AI, a 12-month contract based in Berkeley Heights, NJ, or Alpharetta, GA. Key skills include AWS, data pipelines, and machine learning integration. Local candidates only; W2 employment required.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
July 2, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
On-site
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πŸ“„ - Contract
W2 Contractor
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Berkeley Heights, NJ
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🧠 - Skills detailed
#Data Engineering #"ETL (Extract #Transform #Load)" #Scala #AWS (Amazon Web Services) #SageMaker #AWS SageMaker #Deployment #Data Pipeline #Datasets #ML (Machine Learning) #Data Science #S3 (Amazon Simple Storage Service) #AI (Artificial Intelligence) #Cloud #AWS S3 (Amazon Simple Storage Service) #Monitoring
Role description
NOTE: Need only W2 (Any Visa Except H1B) Please share relevant profiles to Ranjit@cloudingest.com Job Role/Title: Data engineer Lead with Gen AI Contract- 12 Months Location: Berkeley heights NJ or Alpharetta GA-(Only Local) Job Descriptio β€’ nThis team will be working on a data + machine learning platform focused on building recommendation systems and advanced analytics using large-scale merchant datasets β€’ .The goal is not to hire traditional ETL-focused engineers or pure data scientists. Instead, we’re targeting hybrid Data Engineers who can β€’ :Build scalable data pipelines and data model β€’ sWork hands-on with Pytho β€’ nDevelop or integrate machine learning models and inference workflow β€’ sContribute to MLOps pipelines (deployment, monitoring, lifecycle β€’ )Our environment is AWS-centric, and relevant experience is important, particularly β€’ :AWS (S3, Glue, SageMaker, ECS/Fargate β€’ )Working with data platforms like Snowflak β€’ eBuilding data pipelines and ML workflows end-to-en β€’ dThe team will be working on use cases such as β€’ :Building merchant-level analytical datasets and feature pipeline β€’ sPerforming feature engineering and model-ready dataset creatio β€’ nDeveloping recommendation systems (e.g., nearest neighbor, ML-based models β€’ )Supporting model training, evaluation, and inference pipelines in AWS (SageMaker/ECS )At a high level β€’ :The Engineers will execute across data pipelines, feature engineering, and ML integratio β€’ nWithin the pod, we expect a mix of strengths (some stronger in ML, others in core data engineering β€’ )We’ve also included Agentic/LLM-based experience as a β€œnice-to-have”, not a requirementβ€”this helps future-proof the team without narrowing the candidate pool too much β€’ .Key profile we’re targeting β€’ :Data Engineers who can move beyond pipelines and help build systems that generate insights and drive recommendations from dat a