As an Intern Data Engineer - Data Services - 2027, you will join the AI, Analytics, Automation & Data Services practice within an IBM Consulting FutureNow Center. You will work alongside experienced professionals to help organizations modernize data platforms, build scalable data pipelines, and develop AI-driven solutions to improve business performance. Your daily responsibilities include designing, building, testing, and maintaining data integration processes while performing data preparation, transformation, and validation. You will analyze structured and unstructured data to identify trends and support decision-making across industries like healthcare and finance. The role requires proficiency in programming languages such as Python, SQL, and Java, along with a basic understanding of databases, data structures, cloud technologies, machine learning workflows, and ETL/ELT concepts to solve complex enterprise data challenges.
What does a Data Engineer earn?
Median $159000 from 205 postings across 60 companies.
Support data engineering services and AI initiatives to improve business performance and operational efficiency.
Assist in designing, building, testing, and maintaining data pipelines and integration processes.
Perform data preparation, transformation, validation, and quality activities for analytics and AI solutions.
Analyze structured and unstructured data to identify trends and generate actionable insights.
Support the development of modern data platforms and scalable enterprise data architectures.
Test and validate data engineering and analytics solutions to ensure trusted environments.
Contribute to projects that modernize data platforms and automate business processes for diverse clients.
What we're looking for
High School Diploma or GED required.
Bachelor's degree preferred.
Currently pursuing a Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, Analytics, or a related field.
Basic understanding of programming concepts and experience with languages such as Python, SQL, Java, or similar technologies.
Basic understanding of databases, data structures, data processing, analytics, and how data supports business decision-making.
Experience in data preparation, transformation, visualization, analytics, or business problem-solving through coursework, projects, research, hackathons, or other practical learning.
Awareness of Artificial Intelligence, Machine Learning, Generative AI, and emerging technologies.
Familiarity with ETL/ELT concepts, data visualization tools, cloud platforms, machine learning workflows, or modern data architectures (preferred).
Python
SQL
Java
Artificial Intelligence
Machine Learning
Generative AI
Data Engineering
ETL
ELT
Data Visualization
Data Structures
Data Pipelines
Analytics
Databases
Automation
Digital Transformation
Python
SQL
Java
Artificial Intelligence
Machine Learning
Generative AI
Data Structures
Data Processing
Analytics
Business Intelligence
Data Visualization
Databases
Cloud
Python
SQL
AWS
GCP
Azure
Data Pipelines
Microservices
Distributed Systems
API Integration
LLMs
Data Governance
Cloud-Native Design
Data Structures and Algorithms
Python
SQL
PL/SQL
Snowflake
GitHub
ETL
ELT
AWS
Azure
Google Cloud
Data Pipelines
Machine Learning
Generative AI
Tableau
Agile
Data Modeling
NLP
Data Quality