Associate Data Engineer — AI & Data Platforms

IBM; Chicago (IL); On-site; USD 71,000 - 107,000; Full time

Benefits offered by this job

Healthcare benefits

401(k) plan

Paid time off

AI-driven learning platform

Job summary

IBM Consulting is seeking an Associate Data Engineer to design, build, and improve data platforms, products, and services that support analytics, ML, generative AI, and agentic AI solutions.

You will work across data gathering, ingestion, transformation, storage, real-time processing, APIs, dashboards, and governance, collaborating with cross-functional teams to deliver scalable cloud-based data architectures.

Qualifications

• Foundational data engineering concepts: pipelines, databases, APIs, ETL/ELT.
• Basic understanding of cloud computing (AWS/Azure/Google/IBM Cloud).
• Interest in AI/ML, generative AI, agentic AI, or enterprise AI platforms.
• Strong analytical thinking, problem solving, adaptability, teamwork, and communication.
• Willingness to travel up to 100%.

Responsibilities

• Design, build, and improve data platforms, products, and services for analytics, ML and AI solutions.
• Optimize data pipelines, indexes, and data services for performance and data quality.
• Collect, prepare, and analyze structured and unstructured data to provide insights.
• Troubleshoot data quality issues and data-related failures impacting analytics and AI workflows.
• Create dashboards, reports, and observability views for stakeholders.

Skills

Data engineering concepts

Cloud computing concepts

Analytical thinking

Communication

Teamwork

Travel willingness

Education

Bachelor’s degree in related field

Tools

Spark

Hadoop

Kafka

Airflow

dbt

Databricks

Snowflake

Git

Kubernetes

Job description

IBM Consulting is seeking an Associate Data Engineer to design, build, and improve data platforms, products, and services that support analytics, ML, generative AI, and agentic AI solutions.

You will work across data gathering, ingestion, transformation, storage, real-time processing, APIs, dashboards, and governance, collaborating with cross-functional teams to deliver scalable cloud-based data architectures.