Jobs via Dice

AWS DATA ARCHITECT

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Architect on a 3-month contract (potential extension) in a hybrid setting in Clinton, NJ. Requires 12+ years of experience, including 7+ in AWS Data Architecture, with expertise in S3, AWS Glue, and data engineering.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 17, 2026
🕒 - Duration
3 to 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Clinton, NJ
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🧠 - Skills detailed
#IAM (Identity and Access Management) #Lambda (AWS Lambda) #PySpark #Data Modeling #SQL (Structured Query Language) #Data Warehouse #AI (Artificial Intelligence) #Kafka (Apache Kafka) #Metadata #Data Architecture #Amazon Redshift #Python #Snowflake #S3 (Amazon Simple Storage Service) #Redshift #AWS (Amazon Web Services) #BI (Business Intelligence) #AWS Glue #Tableau #Airflow #Data Engineering #Security #dbt (data build tool) #API (Application Programming Interface) #Microsoft Power BI #"ETL (Extract #Transform #Load)" #Microservices #Spark (Apache Spark) #Data Pipeline #Automation #Data Lake
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Turing IT Labs, is seeking the following. Apply via Dice today! Role: AWS Data Architect Location: Hybrid – Clinton, NJ – (3x a week onsite 2 days remote) Employment Type: Contract role Duration: 3 months with Potential Extension. Ideal Candidate Profile • Overall 12+ years of experience, including 7+ years in AWS Data Architecture. • Core AWS Expertise Deep experience with: • S3 (data lake design) • AWS Glue (ETL, catalog) • Amazon Redshift (data warehouse design & optimization) • Lambda, Step Functions (orchestration) • IAM, Lake Formation (security) • Data Engineering & Processing Strong hands-on experience with: • PySpark / Spark (EMR or Glue) • SQL (advanced level) • Python for data pipelines • Experience with streaming (Kinesis / Kafka) is a plus • Data Architecture Expertise in: • Data lake / Lakehouse architectures • Data modeling (dimensional + normalized) • Metadata and cataloguing strategies • Handling large-scale, distributed data systems • Modern Data Stack (Preferred) Exposure to: • DBT, Airflow, Snowflake (optional but valuable) • BI tools (QuickSight, Tableau, Power BI) • API-based ingestion and microservices-based data flows • Amazon Quick Suite (QuickSight, Quick Chat, Quick Flows, Quick Automate, Quick Research) • SQL & Data Modeling • AWS Analytics Stack • Dashboard Design • AI Agent Design & Configuration • Workflow Automation & Business Process Optimization