Data Engineer (on W2)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer in Dallas, TX, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, Java, SQL, and experience with Apache Spark, Hadoop, and ETL workflows.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
-
🗓️ - Date discovered
September 3, 2025
🕒 - Project duration
Unknown
-
🏝️ - Location type
On-site
-
📄 - Contract type
W2 Contractor
-
🔒 - Security clearance
Unknown
-
📍 - Location detailed
Dallas, TX
-
🧠 - Skills detailed
#GCP (Google Cloud Platform) #Airflow #Kafka (Apache Kafka) #Apache Spark #AWS (Amazon Web Services) #Data Modeling #Java #Spark (Apache Spark) #Hadoop #"ETL (Extract #Transform #Load)" #Apache Airflow #Data Science #Scala #Programming #Azure #NoSQL #SQL (Structured Query Language) #Data Engineering #Data Pipeline #Big Data #Cloud #Python
Role description
Data Engineer – Dallas, TX
Role Overview
As a Data Engineer, you’ll be pivotal in designing, building, and maintaining scalable, reliable, and efficient data pipelines and architectures. Your work ensures that data scientists, analysts, and business stakeholders have clean, accessible, and actionable data.
Key Responsibilities
• Design & Develop Data Infrastructure
• Build end-to-end ETL/ELT workflows to source, clean, transform, and load data using tools like Apache Spark, Hadoop, Airflow, and cloud services (e.g., AWS, Azure, GCP).
• Optimize and Maintain Pipelines
• Ensure pipelines are performant, resilient, and scalable—handling large, high-volume workloads.
• Architectural Design & Data Modeling
• Create well-structured data models and warehouses (dimensional modeling, ER diagrams, etc.) to improve data usability and performance.
Required Skills & Qualifications
• Technical Proficiency
• Programming: Python, Java, Scala.
• SQL and DB expertise (relational and NoSQL).
• Big Data tools: Spark, Hadoop, Kafka.
• Workflow tools: Apache Airflow or equivalents.
Data Engineer – Dallas, TX
Role Overview
As a Data Engineer, you’ll be pivotal in designing, building, and maintaining scalable, reliable, and efficient data pipelines and architectures. Your work ensures that data scientists, analysts, and business stakeholders have clean, accessible, and actionable data.
Key Responsibilities
• Design & Develop Data Infrastructure
• Build end-to-end ETL/ELT workflows to source, clean, transform, and load data using tools like Apache Spark, Hadoop, Airflow, and cloud services (e.g., AWS, Azure, GCP).
• Optimize and Maintain Pipelines
• Ensure pipelines are performant, resilient, and scalable—handling large, high-volume workloads.
• Architectural Design & Data Modeling
• Create well-structured data models and warehouses (dimensional modeling, ER diagrams, etc.) to improve data usability and performance.
Required Skills & Qualifications
• Technical Proficiency
• Programming: Python, Java, Scala.
• SQL and DB expertise (relational and NoSQL).
• Big Data tools: Spark, Hadoop, Kafka.
• Workflow tools: Apache Airflow or equivalents.
