Solutions Engineer résumé: what employers are asking for right now
We read 683 open solutions engineer postings on employers' own job boards, at companies including Databricks, Datadog and MongoDB. Of the 394 whose requirements we have read, the skills asked for most are Python (58%), SQL (34%) and AWS (31%) — so those belong near the top of a solutions engineer résumé, in the words the posting uses. The median posting asks for 5+ years of experience.
From 683 open postings on employers’ own job boards, as of .
Skills solutions engineer postings ask for
| Skill | Share of postings | Bar |
|---|---|---|
| Python | 58% | |
| SQL | 34% | |
| AWS | 31% | |
| Azure | 29% | |
| GCP | 28% | |
| APIS | 26% | |
| Distributed Systems | 20% | |
| Databricks | 19% | |
| Cloud Computing | 19% | |
| Kubernetes | 17% | |
| Java | 17% | |
| Pre-sales | 16% | |
| Solutions Architecture | 16% | |
| JavaScript | 15% | |
| SaaS | 15% |
Share of the 394 postings whose requirements we have read.
A skills section built from those postings
List only what you can talk about in an interview, and use the posting’s own words for it — a screener searching for “Python” will not match a synonym. Ordered by how often employers ask:
Skills
Python · SQL
AWS · Azure · GCP · APIS · Distributed Systems · Databricks · Cloud Computing · Kubernetes · Java · Pre-sales · Solutions Architecture · JavaScript · SaaS
- Line 1: asked for by a third or more of postings.
- Line 2: often asked for.
Sample solutions engineer résumé
An illustrative example, not a real person: the employers and results are made up. The skills are the ones the postings above ask for, so it shows how those requirements read on a page.
Senior Solutions Engineer
Senior Solutions Engineer with 8+ years supporting enterprise SaaS and data platforms across pre-sales, architecture, and implementation. Works with Python, SQL, cloud services, and APIs to shape solutions, validate requirements, and move complex deals to production.
Experience
Senior Solutions Engineer · Enterprise data and analytics SaaS company
2021 present
- Partnered with account teams on pre-sales discovery, solution design, and technical validation for multi-cloud deployments.
- Built Python and SQL proofs of concept that connected APIs to cloud data stores and reduced technical evaluation time by 30%.
- Designed reference architectures across AWS, Azure, and GCP, including Kubernetes-based services and distributed systems integration.
- Led workshops for Databricks and Snowflake use cases, translating business requirements into secure SaaS deployment patterns.
Solutions Engineer · Regional workflow automation platform
2017 2021
- Developed JavaScript and Python demos that showed API integrations, data flows, and cloud-native application behavior.
- Supported sales cycles from qualification through security review, aligning solutions architecture to customer technical criteria.
- Created SQL-based validation queries and deployment checks for Azure and AWS environments during pilot and onboarding phases.
- Collaborated with product and engineering teams on Kubernetes, Java, and distributed systems issues raised during customer implementations.
Skills
Python · SQL · AWS · Azure · GCP · APIS · Distributed Systems · Databricks · Cloud Computing · Kubernetes · Java · Pre-sales · Solutions Architecture · JavaScript · SaaS
More solutions engineer bullet points to adapt
- Built Python utilities to automate API testing, cut manual demo setup, and speed response during customer evaluations.
- Mapped customer data pipelines in SQL and cloud services to identify fit, gaps, and implementation risks early in the sales cycle.
- Presented solution architecture for Kubernetes-hosted services, covering scaling, security, and operational ownership.
- Created Databricks proofs of concept that demonstrated ingestion, transformation, and analytics workflows for enterprise prospects.
- Translated technical requirements into pre-sales collateral, including diagrams, demo scripts, and implementation notes.
- Led cloud discovery sessions across AWS, Azure, and GCP to align architecture choices with customer constraints.
- Validated SaaS integrations by testing APIs, authentication flows, and data exchange patterns in sandbox environments.
- Coordinated with engineering on Distributed Systems issues surfaced during customer pilots and production readiness reviews.
What sets an application apart
Listed as a plus rather than a requirement: AWS (20%), Azure (18%), Kubernetes (16%), GCP (12%), Machine Learning (12%), Python (10%), Generative AI (8%) and Data Engineering (7%). Worth naming if you have it, and never worth claiming if you do not.
Level, location and pay
- Most are senior roles (67% of postings that state a level).
- 27% are listed as remote.
- Listed mainly in United States, United Kingdom and Singapore.
- US postings that publish a yearly salary: median $240k, middle half $215k–$258k (from 37 postings).
Who is hiring solutions engineers
- Databricks261 open
- Datadog50 open
- MongoDB41 open
- Stripe28 open
- Elastic25 open
- OpenAI24 open
- Cloudflare20 open
- Cohere17 open
- Fivetran15 open
- Okta14 open
- Decagon13 open
- Sierra13 open