

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, lasting 12 months. Pay is W2. Key skills include Hadoop, Google Cloud, Spark, Kafka, and Python. Public cloud certifications are required, along with data engineering experience and knowledge of data lakehouse architecture.
🌎 - 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 or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables. Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Software Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Software Engineering. Required Qualifications: Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Key Requirements:
Desired Qualifications:
• 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 or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables. Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Software Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Software Engineering. Required Qualifications: Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Key Requirements:
Desired Qualifications:
• 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






