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.
Location: Farmers Branch, TX
Posted: Oct. 2, 2024, 6:52 a.m.
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