

Big Data Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Big Data Engineer with a 12-month contract in Charlotte, NC, Phoenix, AZ, or Irving, TX (Hybrid). Requires 4+ years in software engineering, 3+ years in big data, Apache Spark, Java, and MongoDB expertise.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
June 14, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Charlotte, NC
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π§ - Skills detailed
#Spark (Apache Spark) #Data Pipeline #Data Processing #Programming #Data Quality #Batch #MongoDB #Java #Data Engineering #Scala #Consulting #Security #Apache Spark #Big Data
Role description
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Outstanding long-term contract opportunity! A well-known Financial Services Company is looking for a Big Data Engineer in Charlotte, NC. Phoenix, AZ or Irving, TX (Hybrid).
Work with the brightest minds at one of the largest financial institutions in the world. This is long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.
Contract Duration: 12 Months
Required Skills & Experience
β’ 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
β’ 3+ years of experience in big data engineering role.
β’ Solid skill with Apache Spark (batch and/or streaming).
β’ Strong programming skills in Java.
β’ Experience with MongoDB.
What You Will Be Doing
β’ Design and implement large-scale data processing systems using Apache Spark.
β’ Develop robust, scalable, and high-performance data pipelines.
β’ Integrate and manage data from various sources including MongoDB.
β’ Optimize data workflows for performance, scalability, and reliability.
β’ Ensure data quality, governance, and security best practices are followed.
β’ Monitor and troubleshoot production data pipelines and systems.
Posted By: Blair Richardson