Data Engineering at RTX
Roles, Comp & Culture
An L5 senior data engineer at RTX sits around $127K total comp from 83 verified salary datapoints. The primary Data Engineering tech consists of AWS, Spark and Databricks, according to current job listings. RTX pays data engineers below the other companies we track. Reviews put them at 3.8 on Glassdoor, a little above the middle of the pack. Employee sentiment at RTX reads neutral and employee happiness is trending down over the past year. Layoff risk scores low for the next 30 days. 14 data engineering roles are open right now.
RTX data engineer compensation
Each level's figure is the median of individual RTX 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.
RTX 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 RTX events
Layoffs, leadership changes, and other major moves at the company, with dates.
- Exec departureMar 2026Leadership change
- LayoffDec 2025~1 roles cut
- LayoffOct 2025~2 roles cut
- LayoffJul 2025~102 roles cut
- Exec departureFeb 2025Leadership change
Notable company events we track, with dates.
RTX data engineering tech stack
The languages, storage, and processing tools RTX data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
SQLRTX data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Define integration patterns (e.g., SLT/ODP/CDC, APIs, files, events) between SAP and the analytical stack, balancing latency, cost, reliability, and data quality.
Design and deploy robust batch and streaming ETL/ELT pipelines using PySpark and Python.
Build data pipelines that clean, transform, and aggregate data from disparate sources
Architect, design, and implement scalable cloud-based ETL/ELT solutions using Azure Data Platform technologies including Azure Databricks, PySpark, Azure Data Factory, ADLS, and related Azure services.
Design, build, and maintain data pipelines that ingest, transform, and deliver structured data (databases, ERP/CRM systems, operational systems) and unstructured data such as file shares, SharePoint repositories, images, documents, logs, and engineering artifacts.
Practice for the RTX 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 RTX loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare RTX with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at RTX 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