

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 with Hadoop and Google Cloud, experience with Kafka and Spark, and relevant public cloud certifications. Hybrid work schedule.
🌎 - 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: Participate in low to moderately complex initiatives and identify opportunity for process improvements within Software Engineering. Review and analyze basic or tactical Software Engineering assignments or challenges that require research, evaluation, and selection of alternatives, related to low-to-medium risk deliverables. Present recommendations for resolving low to moderately complex situations and exercise some independent judgment while developing understanding of function, policies, procedures, and compliance requirements. Provide information to 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:
• 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
Desired Qualifications:
• 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: Participate in low to moderately complex initiatives and identify opportunity for process improvements within Software Engineering. Review and analyze basic or tactical Software Engineering assignments or challenges that require research, evaluation, and selection of alternatives, related to low-to-medium risk deliverables. Present recommendations for resolving low to moderately complex situations and exercise some independent judgment while developing understanding of function, policies, procedures, and compliance requirements. Provide information to 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:
• 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
Desired Qualifications:
• 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






