

AWS Cloud Data Engineer - W2
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Cloud Data Engineer in Dallas, TX, for a contract position. Requires 7+ years of data engineering experience, 2-3 years with AWS, strong SQL and Python skills, and knowledge of Apache Airflow.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
520
-
ποΈ - Date discovered
September 25, 2025
π - Project duration
Unknown
-
ποΈ - Location type
On-site
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π - Contract type
W2 Contractor
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π - Security clearance
Unknown
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π - Location detailed
Dallas, TX
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π§ - Skills detailed
#Data Engineering #AWS (Amazon Web Services) #Programming #SQL Queries #Data Migration #Cloud #Datasets #Migration #Airflow #Apache Airflow #Snowflake #Monitoring #Web Services #SQL (Structured Query Language) #Python #Automation
Role description
Job Title: AWS Data Engineer
Location: Dallas, TX
Position Type: Contract position
Job Description:
Client is seeking a Cloud Data Engineer to join the Technology Risk Division of a prominent financial institution. This role is instrumental in orchestrating firmwide liquidity and risk metric calculations, ensuring the organization leverages the right data sets for accurate and strategic decision-making. As part of this team, youβll be responsible for updating and optimizing data sources, enhancing the performance of large-scale datasets, and consolidating data currently stored across multiple platforms into Snowflake. Your work will directly support the firmβs mission to improve risk exposure strategies through robust, cloud-based data engineering.
Required Skills:
β’ 7+ years of experience as a Data Engineer, working with large-scale data systems
β’ 2 - 3 years of hands-on experience with Amazon Web Services (AWS)
β’ Good understanding of Apache Airflow for scheduling and orchestration
β’ Strong proficiency in Python for data engineering and workflow automation
β’ Advanced skills in writing complex SQL queries, especially for data migration into Snowflake
β’ Familiarity with the Software Development Life Cycle (SDLC) especially for python dominated ecosystems.
β’ Excellent communication skills and ability to translate business needs into technical solutions
Nice to Have Skills:
β’ Prior experience with or interest in learning Slang Infrastructure, a proprietary programming language
β’ Familiarity with Amazon MWAA (Managed Workflows for Apache Airflow) for cloud-based workflow orchestration and monitoring.
Thanks!
Job Title: AWS Data Engineer
Location: Dallas, TX
Position Type: Contract position
Job Description:
Client is seeking a Cloud Data Engineer to join the Technology Risk Division of a prominent financial institution. This role is instrumental in orchestrating firmwide liquidity and risk metric calculations, ensuring the organization leverages the right data sets for accurate and strategic decision-making. As part of this team, youβll be responsible for updating and optimizing data sources, enhancing the performance of large-scale datasets, and consolidating data currently stored across multiple platforms into Snowflake. Your work will directly support the firmβs mission to improve risk exposure strategies through robust, cloud-based data engineering.
Required Skills:
β’ 7+ years of experience as a Data Engineer, working with large-scale data systems
β’ 2 - 3 years of hands-on experience with Amazon Web Services (AWS)
β’ Good understanding of Apache Airflow for scheduling and orchestration
β’ Strong proficiency in Python for data engineering and workflow automation
β’ Advanced skills in writing complex SQL queries, especially for data migration into Snowflake
β’ Familiarity with the Software Development Life Cycle (SDLC) especially for python dominated ecosystems.
β’ Excellent communication skills and ability to translate business needs into technical solutions
Nice to Have Skills:
β’ Prior experience with or interest in learning Slang Infrastructure, a proprietary programming language
β’ Familiarity with Amazon MWAA (Managed Workflows for Apache Airflow) for cloud-based workflow orchestration and monitoring.
Thanks!