Associate Data Engineer – Client Innovation Center (Entry Level)
Baton Rouge, LA
Full-time
Onsite
New Grad, Entry Level
IBM Consulting Client Innovation Centers (CICs) are dedicated environments where technologists work collaboratively to develop solutions for clients. The Associate Data Engineer role focuses on supporting the development and maintenance of data pipelines and platforms, while learning from experienced practitioners in a team-based setting.
Support the development and maintenance of data pipelines used for analytics, reporting, and machine learning
Assist with extracting, transforming, and loading (ETL/ELT) data from multiple sources into data platforms
Contribute to data cleansing, validation, and transformation activities using Python and SQL
Help prepare datasets for downstream consumption by analytics and data science teams
Support batch and, where applicable, near-real-time data processing workflows under guidance
Collaborate with data engineers, data scientists, and other team members in Agile delivery environments
Build data engineering skills through training, mentorship, and hands-on delivery experience
Work with functional and technical team members to help integrate data solutions into client business environments
Qualification
Required
Strong foundation in computer science fundamentals, including data structures and algorithms
Strong analytical and problem-solving skills with attention to data quality and reliability
Comfortable working onsite in a collaborative, team-based environment
Ability to work effectively in a technology-driven consulting environment where tools, platforms, and client needs evolve over time
Strong analytical and problem-solving skills, with the ability to approach complex tasks using structured, logical thinking
Ability to learn new systems and technologies quickly and apply them in a delivery setting
Proficiency in Python (preferred) or another programming language used for data processing
Hands-on experience using data manipulation tools such as pandas, NumPy, and SQL, gained through coursework, labs, projects, or internships
Ability to write clear, maintainable code for data transformation and processing tasks
Understanding of ETL/ELT concepts and how data moves from source systems to consumption layers
Familiarity with relational databases and SQL for querying and data manipulation
Basic understanding of data modeling concepts such as schemas, normalization, or dimensional models
Exposure to cloud-based data or analytics platforms (e.g., AWS, Azure, or Google Cloud) through coursework, labs, or projects
Familiarity with core cloud data services such as object storage, databases, or analytics services
Ability to translate business or functional requirements into technical solutions, with guidance from senior team members
Comfortable working onsite in a collaborative, team-based environment
Strong willingness to learn, accept feedback, and continuously improve
Familiarity with generative AI concepts, including basic modeling approaches, responsible use, and ethical considerations, gained through coursework, projects, or self-study
Preferred
Master's Degree
Exposure to distributed data processing tools such as Apache Spark or PySpark
Familiarity with modern data warehouse technologies (e.g., Snowflake, Redshift, BigQuery)
Exposure to streaming or event-based data concepts
Familiarity with version control tools such as Git
Basic awareness of how data engineering supports machine learning workflows
Benefit
IBM is an IT technology and consulting firm providing computer hardware, software, infrastructure, and hosting services.
