Java
Enterprise Java engineering, the largest single area of demand across banking and insurance estates.
The technology stack we recruit and assess against
Every profile we put forward is evaluated against the specific stack your programme runs on — not matched on keywords in a CV. These are the technologies our screening covers for Java developers, .NET developers, cloud engineers, data engineers, DevOps engineers and QA automation specialists.
01 Languages & frameworks
Application engineering
.NET
Microsoft-stack engineering across modernised and long-lived enterprise applications.
Front end
Browser-side engineering for customer channels and internal workbenches.
Services & integration
The connective layer between systems, where most enterprise defects actually live.
Other languages
Where a programme's stack sits outside the two dominant enterprise ecosystems.
Mobile
Customer-facing applications for regulated and consumer-facing organisations.
02 Cloud & platform
Cloud engineering and DevOps
Cloud consulting and platform capability is among the fastest-moving areas we source into, and one where claimed experience and actual production experience differ most. We assess against what a candidate has genuinely operated, not what appears on a certificate.
| Area | Technologies |
|---|---|
| Cloud platforms | AWS, Microsoft Azure, Google Cloud Platform |
| Containers & orchestration | Docker, Kubernetes, OpenShift, Helm |
| Infrastructure as code | Terraform, CloudFormation, Ansible, Pulumi |
| CI/CD | Jenkins, GitLab CI, GitHub Actions, Azure DevOps, Argo CD |
| Observability | Prometheus, Grafana, ELK, Datadog, Splunk, OpenTelemetry |
| Reliability | SRE practice, incident response, capacity planning, DR testing |
03 Data & analytics
Data engineering
| Area | Technologies |
|---|---|
| Pipelines & processing | Apache Spark, Airflow, Kafka Streams, dbt, ETL tooling |
| Warehousing & lakes | Snowflake, Databricks, Redshift, BigQuery, Synapse |
| Databases | Oracle, PostgreSQL, SQL Server, MySQL, MongoDB, Cassandra, Redis |
| Reporting | Power BI, Tableau, Looker, regulatory reporting pipelines |
| Machine learning | Python ML stack, MLOps tooling, model integration and monitoring |
04 Quality & security
QA automation and security engineering
QA automation
- Selenium, Cypress, Playwright and TestNG for functional automation
- REST Assured, Postman and contract testing for service layers
- JMeter, Gatling and k6 for performance and load
- Regression suites, test data management and environment strategy
Cyber security
- Application security, secure code review and SAST/DAST tooling
- Identity and access management, OAuth 2.0, OIDC and SAML
- Vulnerability management and remediation tracking
- Security operations and compliance-driven assurance work
05 Domain platforms
Banking, fintech and insurance platforms
Alongside general engineering skills, we source against the packaged and domain-specific platforms common to financial services estates — core banking, payments and settlement, policy administration, claims, underwriting, trading and post-trade systems. Domain exposure is weighed alongside technical ability, because in these environments the two are not separable.
06 An honest note
A long list is not the same as deep coverage
Every staffing company publishes a technology list like this one. What matters is whether a supplier will tell you when a particular skill is genuinely hard to find. If a requirement sits at the scarce end of any of these areas, we will give you a realistic search timeline rather than an optimistic one — and if we cannot reach it at all, we will say so at the first conversation.
Which stack do you need staffed?
Send the technologies, seniority and working model. We will come back with an assessed shortlist and an indicative rate card.
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