Associate Data Engineer, AI & Data Analytics

IBM

Confirmed live yesterday High trust

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Work type: On-site
Location: —
Posted: 74 days ago
Freshness: Confirmed live yesterday

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How this pay compares to similar roles

Similar $162k

$111k $207k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$197,258.

Based on 240 similar postings.

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

IBM currently has 268 open roles on FindRole.

Listed pay typically runs $187,136–$221,730 across 10 roles with salary data.

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TL;DR · Associate Data Engineer, AI & Data Analytics

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JOB TITLE: Associate Data Engineer 2027 - AI & Data Analytics As an Associate Data Engineer, you will join the IBM Consulting team to design, build, and improve data platforms, products, and services supporting analytics, machine learning, and agentic AI solutions. You will manage data gathering, ingestion, transformation, storage, and real-time processing while ensuring data quality, observability, and governance. Your daily work involves optimizing pipelines, creating dashboards, and troubleshooting complex structured and unstructured datasets to provide actionable insights. You will utilize technologies including Python, SQL, Java, Scala, and JavaScript within cloud environments like AWS, Azure, or IBM Cloud. Key tools include Spark, Kafka, Airflow, dbt, Databricks, Snowflake, and vector databases like Pinecone. You will solve business problems involving RAG, LLM-powered systems, and agent orchestration to create reliable, secure, and governed data interfaces for enterprise systems.

What does a Data Engineer earn?

Median $159000 from 205 postings across 60 companies.

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Skills

Python SQL Java Scala JavaScript AWS Azure Google Cloud IBM Cloud Spark Hadoop Kafka Airflow dbt Databricks Snowflake Delta Lake Linux LangChain LlamaIndex Pinecone Weaviate Kubernetes Git CI/CD RAG LLM ETL ELT

What you'll do

Design and implement scalable data architectures and management systems for cloud environments and AI use cases.
Optimize data pipelines, retrieval indexes, and services to improve performance, reliability, and data quality.
Collect and analyze structured and unstructured data to provide actionable insights for client business practices.
Troubleshoot data quality issues, processing failures, and inconsistencies affecting generative AI or agentic workflows.
Create dashboards and reports to communicate pipeline health and AI system insights to various stakeholders.
Ensure data integrity and security through rigorous cleaning, validation, cataloging, and governance practices.
Translate client requirements into technical specifications for data products, APIs, and operational models.
Resolve complex business problems using technologies like RAG, vector search, and agent orchestration patterns.

What we're looking for

High School Diploma or GED is required.
A Bachelor's degree in a related quantitative field is preferred.
Familiarity with programming or query languages such as Python, SQL, Java, Scala, or JavaScript.
Foundational understanding of data engineering concepts including pipelines, databases, APIs, and ETL/ELT processes.
Basic understanding of cloud computing environments like AWS, Azure, Google Cloud, or IBM Cloud.
Ability to apply foundational statistical, machine learning, or information retrieval concepts to data work.
Experience with tools such as Spark, Hadoop, Kafka, Airflow, dbt, Databricks, Snowflake, or Linux (preferred).
Familiarity with LLMs, vector databases, RAG, and AI agent architectures (preferred).

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