UniFocus
Data Engineer
UniFocus, Carrollton, Texas, us, 75011
Job Type
Full-time
Description
Join our team as a Data Engineer (ETL and Data Modelling) and contribute to our mission of leveraging data to drive meaningful insights and deliver innovative solutions for our clients.
Roles & Responsibilities
Assist in designing, developing, and implementing efficient data models, focusing on Extract, Transform, Load (ETL) processes to ensure performance, scalability, and maintainability.Work closely with senior engineers and cross-functional teams to understand business requirements and support data-driven initiatives.Contribute to the development and maintenance of conceptual, logical, and physical data models while learning best practices and industry standards.Perform data analysis to identify patterns and relationships, and help translate insights into data models that support business needs.Support the implementation of data modeling techniques, such as normalization and indexing, under the guidance of senior team members.Collaborate in integrating data models into ETL processes, ensuring data integrity throughout the pipeline.Partner with database administrators and infrastructure teams to help integrate data models into the overall architecture.Stay updated with new tools and technologies in data engineering and ETL processes, while actively participating in continuous learning.Assist in performance tuning and optimization of existing data models, helping to identify and resolve any issues or bottlenecks.Document data modeling and ETL processes for future reference, contributing to team knowledge sharing.Requirements
Qualifications & Education Requirements
Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent practical experience).Some hands-on experience (internships, projects, or 1-2 years of work experience) in data engineering, data modeling, or ETL processes is a plus.Proficiency in SQL and familiarity with basic data modeling techniques.Analytical and problem-solving mindset with a desire to learn how to translate business requirements into data models.Basic understanding of relational databases and/or NoSQL databases and familiarity with data warehousing concepts.Knowledge of programming languages like Python or Java, with a desire to improve coding skills in a data engineering context.Familiarity with data integration tools and exposure to cloud-based data platforms (AWS, Azure, or Google Cloud) is a plus.Experience or exposure to BI tools like Dundas BI is an added advantage, but not required.Good communication skills with the ability to collaborate with both technical and non-technical stakeholders.Self-motivated, eager to learn, and adaptable to new technologies and best practices in data engineering and ETL.
Full-time
Description
Join our team as a Data Engineer (ETL and Data Modelling) and contribute to our mission of leveraging data to drive meaningful insights and deliver innovative solutions for our clients.
Roles & Responsibilities
Assist in designing, developing, and implementing efficient data models, focusing on Extract, Transform, Load (ETL) processes to ensure performance, scalability, and maintainability.Work closely with senior engineers and cross-functional teams to understand business requirements and support data-driven initiatives.Contribute to the development and maintenance of conceptual, logical, and physical data models while learning best practices and industry standards.Perform data analysis to identify patterns and relationships, and help translate insights into data models that support business needs.Support the implementation of data modeling techniques, such as normalization and indexing, under the guidance of senior team members.Collaborate in integrating data models into ETL processes, ensuring data integrity throughout the pipeline.Partner with database administrators and infrastructure teams to help integrate data models into the overall architecture.Stay updated with new tools and technologies in data engineering and ETL processes, while actively participating in continuous learning.Assist in performance tuning and optimization of existing data models, helping to identify and resolve any issues or bottlenecks.Document data modeling and ETL processes for future reference, contributing to team knowledge sharing.Requirements
Qualifications & Education Requirements
Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent practical experience).Some hands-on experience (internships, projects, or 1-2 years of work experience) in data engineering, data modeling, or ETL processes is a plus.Proficiency in SQL and familiarity with basic data modeling techniques.Analytical and problem-solving mindset with a desire to learn how to translate business requirements into data models.Basic understanding of relational databases and/or NoSQL databases and familiarity with data warehousing concepts.Knowledge of programming languages like Python or Java, with a desire to improve coding skills in a data engineering context.Familiarity with data integration tools and exposure to cloud-based data platforms (AWS, Azure, or Google Cloud) is a plus.Experience or exposure to BI tools like Dundas BI is an added advantage, but not required.Good communication skills with the ability to collaborate with both technical and non-technical stakeholders.Self-motivated, eager to learn, and adaptable to new technologies and best practices in data engineering and ETL.