

Ampstek
Data Engineer (GCP + ODL + Big Query + Big Data + SQL)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with strong expertise in GCP, BigQuery, and Big Data technologies. It is a 12+ month onsite contract in Phoenix, AZ, requiring advanced SQL skills and experience with ETL processes and tools like ODL.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 5, 2026
🕒 - Duration
More than 6 months
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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
Phoenix, AZ
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Cloud #GCP (Google Cloud Platform) #Data Science #Spark (Apache Spark) #Data Engineering #Data Pipeline #Data Analysis #Hadoop #Scala #Data Quality #Data Architecture #BigQuery #Oracle #Datasets #SQL Queries #Data Modeling #Big Data #SQL (Structured Query Language) #Data Extraction #BI (Business Intelligence)
Role description
Role: Data Engineer (GCP + ODL + Big Query + Big data + SQL)
Location: Phoenix, AZ(Onsite)
Job Type: 12+ Months Contract
Job Description:
We are looking for a skilled Data Engineer with strong experience in Google Cloud Platform (GCP), BigQuery, and Big Data technologies. The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and data architectures to support analytics and business intelligence needs.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines on GCP
• Work with BigQuery for data warehousing, transformation, and performance optimization
• Develop and manage ETL/ELT processes using tools like ODL (Oracle Data Loader/Integrator)
• Handle large-scale datasets using Big Data technologies such as Hadoop, Spark, or Hive
• Write efficient and optimized SQL queries for data extraction and analysis
• Collaborate with data analysts, data scientists, and business stakeholders
• Ensure data quality, integrity, and governance across systems
• Monitor and troubleshoot data workflows and pipelines
Required Skills:
• Strong experience with Google Cloud Platform (GCP)
• Hands-on experience with BigQuery
• Expertise in SQL (advanced level)
• Experience with Big Data tools (Hadoop, Spark, Hive, etc.)
• Knowledge of ETL/ELT processes and tools (ODL preferred)
• Understanding of data modeling and data warehousing concepts
Thanks & Regards
Himanshu Verma | Recruiter – US Staffing
Email: Himanshu.v@ampstek.com | Desk: (609)-527-8914
Ampstek LLC – Global IT Partner | www.ampstek.com
Role: Data Engineer (GCP + ODL + Big Query + Big data + SQL)
Location: Phoenix, AZ(Onsite)
Job Type: 12+ Months Contract
Job Description:
We are looking for a skilled Data Engineer with strong experience in Google Cloud Platform (GCP), BigQuery, and Big Data technologies. The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines and data architectures to support analytics and business intelligence needs.
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines on GCP
• Work with BigQuery for data warehousing, transformation, and performance optimization
• Develop and manage ETL/ELT processes using tools like ODL (Oracle Data Loader/Integrator)
• Handle large-scale datasets using Big Data technologies such as Hadoop, Spark, or Hive
• Write efficient and optimized SQL queries for data extraction and analysis
• Collaborate with data analysts, data scientists, and business stakeholders
• Ensure data quality, integrity, and governance across systems
• Monitor and troubleshoot data workflows and pipelines
Required Skills:
• Strong experience with Google Cloud Platform (GCP)
• Hands-on experience with BigQuery
• Expertise in SQL (advanced level)
• Experience with Big Data tools (Hadoop, Spark, Hive, etc.)
• Knowledge of ETL/ELT processes and tools (ODL preferred)
• Understanding of data modeling and data warehousing concepts
Thanks & Regards
Himanshu Verma | Recruiter – US Staffing
Email: Himanshu.v@ampstek.com | Desk: (609)-527-8914
Ampstek LLC – Global IT Partner | www.ampstek.com






