Data Engineering at Bank of America
Roles, Comp & Culture
An L5 senior data engineer at Bank of America sits around $160K total comp from 61 verified salary datapoints. The primary Data Engineering tech consists of Docker, Hadoop and Hive, according to current job listings. Bank of America pays data engineers in line with other Finance companies. Reviews put them at 3.9 on Glassdoor, a little above the middle of the pack. Employee sentiment at Bank of America reads neutral and employee happiness has held flat over the past year. Layoff risk scores low for the next 30 days. 1 data engineering role is open right now.
Bank of America data engineer compensation
Each level's figure is the median of individual Bank of America offers at that level, so it reflects a typical outcome rather than an average pulled up by a few large packages. Total comp counts base salary plus equity and bonus annualized over the vest, and the range shown is the middle half of offers, with the top and bottom quarters trimmed off.
Bank of America employee sentiment, tracked weekly
Employee happiness for data engineers over the past year, so you can see which direction it is moving, not just where it sits today.
The trade Bank of America offers is stability in exchange for pace. Pay at L5 sits at $160K, in line with other Finance companies, so you're not leaving money on the table relative to finance peers, but you're not seeing the comp spikes that come from high-growth tech shops. The 3.9 Glassdoor rating is a little above the middle of the pack, and sentiment on Blind runs mixed, which tracks with what the happiness data shows: engineers here are neutral, with signals roughly flat. The tension is that BofA's engineering culture moves at a bank's cadence, not a startup's. Teams that own critical pipelines get resources and job security; engineers who want to ship fast and iterate in public will find the approval layers genuinely frustrating.
Hiring volume is thin right now: 1 open data engineering role, concentrated in Charlotte. That's a small footprint for an institution this size, which suggests data engineering headcount is largely filled and the bank is backfilling rather than expanding. The 30 day layoff risk reads as low, consistent with a regulated institution that moves employment slowly in both directions. The roughly flat happiness trend is worth watching; it doesn't indicate a crisis, but it does suggest the internal engineering environment has been under some pressure, possibly from modernization programs that create churn without yet delivering wins. Someone joining now enters a relatively stable seat but should expect the org to stay roughly this size over the next year.
Bank of America data engineering tech stack
The languages, storage, and processing tools Bank of America data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
Bank of America's core data problem is scale married to regulation. The bank processes hundreds of millions of transactions daily across consumer banking, wealth management, trading, and corporate lending, and every pipeline that touches that data carries compliance obligations: Basel III reporting, CCAR stress testing, AML monitoring, and FINRA recordkeeping. That regulatory surface shapes the engineering work more than the volume alone does. The stack shows Docker, Hadoop and Hive, which points toward a mature, on-premises-rooted infrastructure that the bank has been gradually containerizing rather than replacing. Data engineers here are more likely to own the reliability and governance layer of existing pipelines than to greenfield new ones, and the modeling work tends to center on risk, customer, and transaction domains where correctness is non-negotiable.
Bank of America data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
The salary data tells you something about who actually gets hired here: 61 reports at the mid band versus 5 at senior, out of 66 total. BofA fills the mid-level role heavily and promotes carefully. Engineers who do well here tend to have patience for process-heavy environments, genuine interest in financial data domains (risk models, transaction lineage, regulatory feeds), and comfort owning pipelines that cannot go down. The interview concentrates on data modeling in the loop and Python at the screen, so prep your SQL and modeling fundamentals before anything else. If you want fast iteration cycles, a modern lakehouse stack, or equity upside, pass. If you want a durable seat working on consequential financial infrastructure with peers who take data quality seriously, check the open roles and prep for the pipeline architecture loop.
Preparing for the Bank of America loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare Bank of America with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at Bank of America interview difficulty
- 01
Reading a solution is not the same as writing one
Every engineer who has frozen on a query they had read a dozen times knows the gap. The only preparation that closes it is producing the answer yourself, under time, before the interview does it for you
- 02
76% of hiring managers reject on the coding task, not the resume
From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice
- 03
5 problem shapes cover 80% of data engineer loops
Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition