Data Engineer Intern 2027

Introduction Launch yourcareer like an IBMer Every IBMer has a story. For many, it started with an internship. As an IBM intern, you won't just gain experience - you'll start thinking, working, and growing like an IBMer. From day one, you'll contribute to real client projects across diverse industries, working alongside experienced IBMers who are invested in your success. You'll be challenged, supported, and inspired, often all in the same day. You'll develop technical expertise and consulting skills in a culture built on continuous learning, mentorship, and coaching. High-performing interns have a clear pathway into IBM's Associate Program, launching careers at one of the world's most innovative technology and consulting companies. To give yourself the best opportunity for success, we advise applying only to roles that align with your skills and experience, rather than applying broadly across all entry-level positions. You'll receive a status update email for each application, so be sure to check your IBM Careers account regularly — it's the best way to get a centralized view of which roles you have active applications against. Your Role And Responsibilities During your internship, you can enhance your knowledge and gain professional experience by working on client projects. This role provides an exceptional opportunity to build a compelling portfolio, acquire new skills, gain insights into diverse industries, and embrace novel challenges for your future career. At IBM, we prioritize continuous learning, skill development, and personal growth within a culture of coaching and mentorship. As an intern, you'll experience this culture and could advance to our full-time Associates program based on results and performance. Work Experiences You Could Be Exposed To Mentored Analytical Support: Receive mentorship from diverse professionals in science, engineering, and consulting, applying analytical rigor and statistical methods to predict behaviors. Data Integrations: Develop skills in writing efficient and reusable programs to cleanse, integrate, and model data. Evaluate model results contributing to data-driven insights. Effective Communication: Assisting in conveying analytical results to both technical and non-technical audiences, refining your ability to communicate complex findings. Tech-Driven Data Transformer: Utilize program languages like Python to build data pipelines, extracting and transforming data from repositories to consumers. Gain exposure to cloud platforms, ETL tools, and data integration, expanding your tech toolkit. Preferred Education Bachelor's Degree Required Technical And Professional Expertise Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, or a related field (Preferred majors include Data Science, Data Engineering, MIS, Business Analytics, Computer Engineering, Computer Science, Statistics, Mathematics, Engineering, Systems Engineering, Industrial Engineering, or a related field. Strong interpersonal skills that enhance collaboration and relationship building, while also managing dynamic workloads in an agile environment. Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints. Demonstrate leadership experience and ability to communicate effectively through active listening, while also being willing to adapt and have a readiness to take ownership of tasks and challenges. Familiarity with one or more scripting languages (Python preferred), or a proven computer science foundation. Willingness to travel as needed. Preferred Technical And Professional Experience Demonstrate familiarity or interest in statistical analysis or data mining through previous internships, personal/academic projects, hackathons, and/or publications. General familiarity with databases, data-engineering tools (SQL, Spark) and cloud platforms (e.g., IBM Cloud, Azure, AWS). Experience with NLP/LLM/GenAI is a plus. Exposure to programming languages (e.g., JavaScript, SQL, Python) and basic understanding of Hybrid Cloud (IBM Cloud, AWS, Azure, Snowflake, Databricks,etc) and AI concepts. #J-18808-Ljbffr IBM