Internship/Co-Op, Data Engineer

Key Responsibilities

• Develop and enhance data pipeline solutions for product features, technical roadmaps, analytics, and AI use cases.
• Build data ingestion, transformation, validation, and integration processes for laser-machine and enterprise data.
• Contribute to automated continuous data integration pipelines for building, testing, and releasing data solutions.
• Develop and optimize SQL transformations, data models, and analytical datasets.
• Apply systematic problem-solving to identify root causes, resolve technical issues, and standardize reusable solutions.
• Collaborate with cross-functional engineering and business teams on system design changes and improvements to system performance.
• Work with business users to understand requirements and translate business goals into feasible technical solutions.
• Collaborate with data architects, software engineers, AI engineers, and IT team members to achieve shared project goals.
• Help improve data quality, observability, monitoring, lineage, and governance.
• Apply industry practices for code quality, automated testing, version control, maintainability, and technical documentation.
• Refactor and improve existing code for coexistence of legacy and modern systems during technology transitions.
• Participate in code reviews, technical design discussions, agile delivery activities, and continuous improvement.
• Document data pipelines, interfaces, data models, decisions, dependencies, and operating procedures.
• Contribute reusable data components and engineering patterns supporting multiple teams and use cases.

Requirements & Tech Stack

• Pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, Software Engineering, or a related field.
• Knowledge of or experience with Python, SQL, Java, or a comparable programming language.
• Knowledge of relational databases, data modeling, and data integration concepts.
• Familiarity with Databricks, SQL Server, or other database and data-platform technologies.
• Familiarity with Microsoft Azure or another cloud environment.
• Exposure to ETL/ELT development, data pipelines, or analytical data processing.
• Academic, personal, or professional project experience performing data engineering or similar work.
• Familiarity with Git, automated testing, CI/CD, or modern software-development practices is preferred.
• Experience with data quality, pipeline monitoring, or data visualization is a plus.

Skills and Competencies

• Strong customer focus and commitment to customer satisfaction.
• Strong numerical, analytical, and structured problem-solving skills.
• Ability to decompose complex problems, clarify requirements, and propose feasible solutions.
• Attention to detail and ability to complete assignments with high accuracy.
• Ownership and accountability for assigned work, including raising risks and following through on commitments.
• Ability to perform effectively in a demanding environment with changing priorities and workloads.
• Open, clear, concise, and professional communication.
• Ability to establish cooperative working relationships with colleagues, technical teams, and business stakeholders.
• Willingness to seek feedback, learn new technologies, and continuously improve.
• Understanding of code health, testing, maintainability, and documentation.
• Ability to balance immediate delivery needs with the development of scalable and reusable solutions.