

Wells Fargo
Senior Data Engineer (contract)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer in Phoenix, AZ, on a 12-month W2 contract. Key skills include data engineering, Hadoop, Google Cloud solutions, and public cloud certifications. Experience with data lakehouse architecture and data migration is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
August 6, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Phoenix, AZ
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🧠 - Skills detailed
#Docker #Data Pipeline #Kafka (Apache Kafka) #NoSQL #Azure #GIT #Data Governance #SQL (Structured Query Language) #Compliance #Data Migration #Jenkins #Deployment #Storage #Python #React #Airflow #BigQuery #Graph Databases #Consulting #Data Engineering #Data Lakehouse #AWS (Amazon Web Services) #HDFS (Hadoop Distributed File System) #Scala #Data Warehouse #Public Cloud #PySpark #Databases #Kubernetes #GCP (Google Cloud Platform) #Migration #Hadoop #Data Lake #Spark (Apache Spark) #Cloud #Apache Kafka #Langchain
Role description
Description
Title: Senior Data Engineer
Location: Phoenix, AZ
Duration: 12 months
Work Engagement: W2
Work Schedule: Hybrid 3 days in office/2 days remote
Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits
Summary:
In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Key Requirements:
• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.
• Experience in data engineering including hands-on experience working with Hadoop and Google Cloud data solutions: creating/supporting Spark based processing, Kafka streaming, in a highly collaborative team
• Hands-on experience developing data flows using Kafka, Flink, and Spark streaming
• Experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Apache Kafka, Airflow, and SQL, GPC Cloud Storage, BigQuery, Data Proc, Cloud Composer
• Working with NoSQL databases such as columnar databases, graph databases, document databases, KV stores, and associated data formats
• Public cloud certifications such as GCP Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics
• Proven skills with data migration from on-prem to a cloud native environment
• Proven experience working with the Hadoop ecosystem capabilities such as Hive, HDFS, Parquet, Iceberg, and Delta Tables
• Deep understanding of data warehouse, data cloud architecture, building data pipelines, and orchestration
• Design and implementation of highly scalable and modular data pipelines with built-in data controls for automating data governance
• Familiarity of GenAI frameworks such as Langchain and Langraph to develop agent-based data capabilities
• Dev Ops and CI/CD deployments including Git, Jenkins, Docker, and Kubernetes
• Web based UI development using React and Node JS is a plus
Description
Title: Senior Data Engineer
Location: Phoenix, AZ
Duration: 12 months
Work Engagement: W2
Work Schedule: Hybrid 3 days in office/2 days remote
Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits
Summary:
In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Key Requirements:
• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.
• Experience in data engineering including hands-on experience working with Hadoop and Google Cloud data solutions: creating/supporting Spark based processing, Kafka streaming, in a highly collaborative team
• Hands-on experience developing data flows using Kafka, Flink, and Spark streaming
• Experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Apache Kafka, Airflow, and SQL, GPC Cloud Storage, BigQuery, Data Proc, Cloud Composer
• Working with NoSQL databases such as columnar databases, graph databases, document databases, KV stores, and associated data formats
• Public cloud certifications such as GCP Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics
• Proven skills with data migration from on-prem to a cloud native environment
• Proven experience working with the Hadoop ecosystem capabilities such as Hive, HDFS, Parquet, Iceberg, and Delta Tables
• Deep understanding of data warehouse, data cloud architecture, building data pipelines, and orchestration
• Design and implementation of highly scalable and modular data pipelines with built-in data controls for automating data governance
• Familiarity of GenAI frameworks such as Langchain and Langraph to develop agent-based data capabilities
• Dev Ops and CI/CD deployments including Git, Jenkins, Docker, and Kubernetes
• Web based UI development using React and Node JS is a plus






