Dallas Onsite Data Engineer: ETL, Data Warehouse & ML

Qualis1 Inc.; Dallas (TX); On-site; USD 100,000 - 160,000; Full time

Job summary

Qualis1 Inc. in Dallas, TX is seeking a data engineer to design and implement data warehouse solutions and advanced analytical applications.

You will apply engineering science and best practices to build scalable pipelines, support AI/ML capabilities, and ensure performance and reliability. You will collaborate with data scientists and analysts, perform data migrations, implement security controls, and optimize ETL processes using Spark, Hadoop, and cloud services.

Qualifications

• Strong knowledge of data engineering principles and practices.
• Proficiency in Python, Java, or Scala and SQL.
• Experience with big data platforms such as Spark or Hadoop.
• Knowledge of database design and data modeling.
• Understanding of ETL and data integration concepts.

Responsibilities

• Apply engineering science and technology to design and implement data warehouse and analytical applications.
• Enhance and maintain corporate data warehouse and analytical platforms.
• Support advanced analytics capabilities including ML, predictive modeling, and AI.
• Debug, test, and optimize data pipelines and ETL processes for performance and reliability.
• Design and implement scalable, compliant data architectures.
• Collaborate with data scientists and analysts to deploy analytics solutions.
• Implement data security, encryption, and access control mechanisms.
• Support data migration and integration projects.

Skills

Data engineering

Python/Java/Scala

SQL

ETL concepts

Data modeling

Tools

Spark

Hadoop

Cloud data services

Job description

Qualis1 Inc. in Dallas, TX is seeking a data engineer to design and implement data warehouse solutions and advanced analytical applications.

You will apply engineering science and best practices to build scalable pipelines, support AI/ML capabilities, and ensure performance and reliability. You will collaborate with data scientists and analysts, perform data migrations, implement security controls, and optimize ETL processes using Spark, Hadoop, and cloud services.