Data Engineer - Remote

About the Role

IBM Consulting is seeking an Intern Data Engineer to join its AI, Analytics, Automation & Data Services practice for 2027. As part of the IBM Consulting FutureNow Center, you will work alongside experienced data engineers, AI specialists, technology professionals, and business teams to help solve real-world client challenges involving data engineering, analytics, automation, cloud technologies, and Artificial Intelligence. This internship provides hands-on exposure to modern data platforms, data pipelines, data integration, analytics, and AI-driven solutions across industries such as healthcare, financial services, retail, manufacturing, government, and energy. Through mentorship, structured learning, project experience, and AI-enabled tools, you will build technical, analytical, problem-solving, communication, teamwork, and consulting skills that can support a future career with IBM Consulting.

Key Responsibilities

• Support data engineering services and AI initiatives that improve business performance, operational efficiency, and data-driven decision-making.
• Assist experienced team members in designing, building, testing, and maintaining data pipelines, data integration processes, and modern data platforms.
• Contribute to data preparation, transformation, validation, and quality activities supporting analytics, automation, and AI solutions.
• Analyze structured and unstructured data to identify trends, generate insights, and support business decisions.
• Collaborate with cross-functional business and technology teams on data, analytics, cloud, and AI initiatives.
• Gain exposure to enterprise data architectures, cloud platforms, analytics technologies, and Artificial Intelligence solutions.
• Assist with testing, validating, and supporting data engineering and analytics solutions.
• Support the development of trusted and scalable data environments.
• Participate in project meetings and workshops.
• Participate in professional development opportunities to strengthen communication, teamwork, and consulting skills.

Required Qualifications

• Currently pursuing a Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, Analytics, or a related field.
• Interest in data engineering, Artificial Intelligence, analytics, automation, cloud technologies, or digital transformation.
• Basic understanding of programming concepts with exposure to Python, SQL, Java, or similar technologies through coursework, projects, research, internships, or personal learning.
• Basic understanding of databases, data structures, data processing, analytics, and how data supports business decision-making.
• Exposure to data preparation, transformation, visualization, analytics, or business problem-solving through coursework, academic projects, research, hackathons, student organizations, personal learning, certifications, IBM SkillsBuild, volunteer experiences, or other practical learning.
• Awareness of Artificial Intelligence, Machine Learning, Generative AI, and emerging technologies and their impact on business and digital transformation.
• High School Diploma/GED.

Preferred Qualifications

• Exposure to data engineering, analytics, automation, Artificial Intelligence, cloud technologies, or enterprise data platforms through coursework, student projects, research, hackathons, or internship experience.
• Familiarity with databases, SQL, ETL/ELT concepts, data visualization tools, cloud platforms, machine learning workflows, or modern data architectures.
• Interest in Artificial Intelligence, Generative AI, data-driven decision-making, consulting, and continuous learning.
• Ability to collaborate effectively with teammates while supporting data modernization, analytics, and enterprise AI transformation initiatives.

Skills & Competencies

• Data engineering
• Python
• SQL
• Java or similar programming technologies
• Database fundamentals
• Data structures and data processing
• Data preparation and transformation
• Data validation and data quality
• Data analytics
• Data visualization
• ETL/ELT concepts
• Artificial Intelligence
• Machine Learning
• Generative AI
• Cloud technologies
• Modern data platforms and architectures
• Automation
• Problem-solving
• Analytical thinking
• Business decision-making
• Communication
• Teamwork and collaboration
• Consulting skills
• Growth mindset
• Curiosity and continuous learning

Education & Experience

Education: Currently pursuing a Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, Analytics, or a related field. A High School Diploma/GED is also listed as a required education qualification.

Experience: No specific professional experience or years of experience are required. Relevant exposure may come through coursework, academic projects, research, hackathons, internships, student organizations, personal learning, certifications, IBM SkillsBuild, volunteer experiences, or similar practical learning opportunities.