Associate Data Engineer: Build AI-Driven Data Platforms

IBM; San Francisco (CA); On-site; USD 71,000 - 107,000; Full time

Job summary

IBM is seeking an Associate Data Engineer in California to design, build, and improve data platforms and services that support analytics, AI, and machine learning initiatives. You will work across data gathering, ingestion, transformation, storage, and real-time processing while ensuring data quality and governance.

You will collaborate with diverse teams, leverage modern data stack tools, and contribute to scalable cloud-based data architectures that power AI-enabled decision making.

Qualifications

• Foundational understanding of data engineering concepts and data pipelines.
• Basic understanding of cloud computing environments (AWS/Azure/Google Cloud/IBM Cloud).
• Ability to apply basic statistical or ML concepts to data tasks.
• Interest in AI/ML, generative AI, or enterprise AI platforms.
• Strong analytical thinking, problem solving, and teamwork.

Responsibilities

• Design, build, and improve data platforms, products, and services supporting analytics and AI solutions.
• Optimize data pipelines and data services for performance, reliability, and data quality.
• Collect and analyze structured and unstructured data to provide actionable insights.
• Collaborate with clients, architects, and AI engineers to translate requirements into solutions.
• Establish data governance, lineage, and observability across pipelines and systems.

Skills

Data pipelines

Databases

APIs

ETL/ELT

Data modeling

Cloud computing basics

AI/ML interest

Teamwork

Communication skills

Education

High School Diploma/GED

Bachelor's Degree

Tools

Spark

Hadoop

Kafka

Airflow

dbt

Databricks

Snowflake

Delta Lake

Linux

Job description

IBM is seeking an Associate Data Engineer in California to design, build, and improve data platforms and services that support analytics, AI, and machine learning initiatives. You will work across data gathering, ingestion, transformation, storage, and real-time processing while ensuring data quality and governance.

You will collaborate with diverse teams, leverage modern data stack tools, and contribute to scalable cloud-based data architectures that power AI-enabled decision making.