Data Engineering at BlackRock
Roles, Comp & Culture
An L4 mid data engineer at BlackRock sits around $181K total comp from 18 verified salary datapoints. The primary Data Engineering tech consists of Snowflake, Azure and dbt, according to current job listings. BlackRock pays data engineers slightly above other Finance companies. Reviews put them at 3.8 on Glassdoor, a little above the middle of the pack. Employee sentiment at BlackRock reads neutral and employee happiness is trending down over the past year. Layoff risk scores low for the next 30 days. 18 data engineering roles are open right now.
BlackRock data engineer compensation
Each level's figure is the median of individual BlackRock 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.
BlackRock 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.
Recent BlackRock events
Layoffs, leadership changes, and other major moves at the company, with dates.
- LayoffMay 2026Layoff
- Exec departureJan 2026Leadership change
- Exec departureFeb 2025Leadership change
- Exec departureJan 2025Leadership change
Notable company events we track, with dates.
BlackRock data engineering tech stack
The languages, storage, and processing tools BlackRock data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
SQL
FivetranBlackRock data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Architect and oversee the development of scalable, reliable data pipelines and analytics platforms, with accountability for end-to-end technical design, data, and long-term sustainability, with a strong focus on Snowflake, SQL, and Python.
EDP powers the acquisition, processing, governance, and distribution of data across Aladdin and BlackRock, enabling everything from investment workflows and analytics to AI-driven solutions.
Build and optimize large-scale data pipelines supporting data ingestion, transformation, validation, and distribution across enterprise cloud environments.
Design and build solutions which are performant, consistent, and scalable
Develop backend services using Python-based frameworks such as FastAPI or Flask, and contribute to contract-first API development using gRPC and Protocol Buffers.
Design, develop, and own end‑to‑end features across data pipelines, APIs, and microservices, from ingestion and transformation through consumption.
At least 6+ years of experience as a data integration engineer with medium to large scale systems, preferably in a financial services or trading environment
Automate manual ingest processes and optimize data delivery subject to service level agreements; work with infrastructure on re-design for greater scalability.
Design and develop reliable ELT/ETL pipelines across Snowflake and SQL Server to support both scheduled batch loads and low-latency ingestion where needed.
Knowledge of Extract-Transform-Load (ETL) and big data analytics tools
Practice for the BlackRock loop
Round by round, the problems our model predicts for this company's interview. Rehearse the shapes their panels keep returning to.
Preparing for the BlackRock loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare BlackRock with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at BlackRock 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