got a recruiter reach-out for a senior data engineer role at IBM, it's on the Hybrid Cloud side. screening call done, she said there's an OA then 3 more rounds.
would love to hear from anyone who's done a data engineering loop at IBM recently. specifically curious: what does the technical round look like? sql heavy, spark/python coding, system design, or something else? are the behavioral rounds as STAR-rigid as people say? any IBM-specific framework or competency language i should know going in?
my background is heavily Spark and Airflow. not sure if that maps well to IBM's internal tooling or if i need to brush up on anything IBM-specific.
4 replies
ds_dmitri
went through a Data Scientist loop at IBM last year, probably adjacent enough to be useful. the technical round was SQL-heavy with a design question about building a data pipeline for a hypothetical retail analytics use case. they weren't testing exotic Spark internals, more can you reason about the end-to-end problem. knowing their cloud stack (IBM Cloud, Db2) doesn't hurt but they don't assume you have it.
de_derek
helpful, thanks. Db2 is one of those things i haven't touched since a job 4 years ago. probably worth a quick refresh on the query syntax differences.
infra_ines
the IBM behavioral rubric is real, they follow it closely. i'd look up IBM's 'Think' values and practice framing your stories in that language. it sounds a little corporate but the interviewers genuinely listen for it. 'client focus', 'courage', 'continuous learning'. just fold those into your STAR wrap-ups without being weird about it.
staff_steph
IBM does have a few internal tools (DataStage, for one) that come up in certain DE roles. if the job description mentions it, worth a glance. if it doesn't, you're probably fine staying on open-source stack framing. they're aware they can't out-tool AWS/GCP in candidate familiarity.