Portfolio of Keith Elder

Engineering Skills Assessment

by Keith Elder

Skills Assessment

Establishing a clear baseline of technical capability is essential for helping team members understand their strengths and identify opportunities for growth. One method I’ve used successfully as a leader for more than a decade is a structured skills assessment. The rating system below provides a consistent way to evaluate a team member’s current proficiency and highlight areas to develop moving forward. This approach is especially valuable when inheriting teams during reorganizations, where members were originally interviewed or evaluated by someone else.

Team members should complete the initial assessment and review it with their leader. Reassessing every six months allows both parties to track progress, document growth, and ensure development efforts stay aligned with evolving team and organizational needs.

Technology & Engineering Skills Assessment Template

This assessment is designed to help engineering teams identify strengths, gaps, and development opportunities across core technology domains.
Each team member should rate their proficiency using the standardized scale below.

Proficiency Scale (0–9)

LevelLabelDescription
0No AwarenessNever heard of the technology.
1Basic AwarenessKnow what it is but have never used it.
2Light ExplorationPlayed with it for a few hours or did a tiny experiment.
3Learning ModeCompleted tutorials or training; no production use yet.
4Limited Production ExposureUsed lightly in production OR helped support something using it.
5Regular Production UserUse it in production with confidence; have supported real issues.
6Advanced Production ExperienceDeep production experience; trusted by peers to troubleshoot, optimize, and deliver with it.
7Senior-Level ExpertiseCan architect solutions, diagnose complex issues, and define best practices with it.
8Expert / Mentor / ContributorMentor others, teach, present, write, or contribute back to the community/OSS for this tech.
9Global-Level ExpertRecognized authority or thought leader; major contributions, widely used content, or frameworks.

For each item below, rate yourself 0–9.

SECTION 1 — Networking Fundamentals

Networking Protocols

  • DNS (port 53, UDP/TCP) — __

  • TCP/IP (routing, ports, sockets) — __

  • UDP ("fire and forget") — __

  • SMTP (email, port 25) — __

  • HTTP (port 80, verbs, headers, cookies) — __

  • HTTPS (port 443, TLS/SSL) — __

  • FTP (port 21) — __

  • SFTP (port 22) — __

  • SSH (port 22) — __

Network Infrastructure

  • Firewalls / Security Groups — __

  • VPNs — __

  • Load Balancers (L4/L7) — __

  • Reverse Proxies (NGINX, Envoy, HAProxy, etc.) — __

  • DNS management (Route53, Cloudflare, etc.) — __

SECTION 2 — Infrastructure & Cloud

Containerization & Orchestration

  • Docker — __

  • Kubernetes — __

  • Helm — __

  • Container registries (ECR, ACR, GCR, GHCR) — __

Cloud Providers

  • AWS — __

  • Azure — __

  • GCP — __

Compute / Storage / Networking

  • Virtual machines / EC2 / VM Scale Sets — __

  • Object storage (S3, Blob Storage, GCS) — __

  • IAM / RBAC — __

  • VPC / VNets / Subnets — __

  • Private networking / peering — __

SECTION 3 — Hardware & Operating Systems

Hardware

  • PC hardware (building / upgrading) — __

  • Mac hardware ecosystem — __

Operating Systems

  • Windows — __

  • macOS — __

  • Linux (Ubuntu, RHEL, Amazon Linux, etc.) — __

  • BSD — __

Shell & Scripting

  • Bash / zsh scripting — __

  • Windows scripting (PowerShell) — __

SECTION 4 — Programming Languages

Rate overall proficiency (syntax, idioms, debugging, and production use).

  • HTML — __

  • CSS — __

  • JavaScript — __

  • TypeScript — __

  • Node.js — __

  • Angular — __

  • React — __

  • C# / .NET — __

  • Java — __

  • Go — __

  • Rust — __

  • Python — __

  • PHP — __

  • Perl — __

  • PowerShell — __

  • Bash — __

  • SQL — __

SECTION 5 — Frameworks & Application Development

  • ASP.NET / ASP.NET Core — __

  • Entity Framework / Dapper — __

  • Spring / Spring Boot — __

  • Express.js — __

  • Flask / FastAPI / Django — __

  • Serverless frameworks (Lambda, Functions, etc.) — __

  • SPA frameworks (Angular/React/Vue) — __

SECTION 6 — Databases & Data Systems

Relational Databases

  • MS SQL Server — __

  • PostgreSQL — __

  • MySQL — __

  • Oracle — __

NoSQL / Key-Value

  • DynamoDB — __

  • MongoDB — __

  • Redis — __

  • Cassandra — __

Data Engineering Concepts

  • ETL / ELT — __

  • Streaming platforms (Kafka, Kinesis, EventHub) — __

  • Data lakes — __

  • Data warehouses (Snowflake, Redshift, BigQuery, Synapse) — __

SECTION 7 — DevOps, CI/CD & Observability

CI/CD Pipelines

  • Azure DevOps Pipelines — __

  • GitHub Actions — __

  • Jenkins — __

  • ArgoCD / FluxCD — __

Infrastructure as Code

  • Terraform — __

  • CloudFormation — __

  • Pulumi — __

Monitoring & Logging

  • Prometheus — __

  • Grafana — __

  • ELK / OpenSearch — __

  • CloudWatch / Azure Monitor / Stackdriver — __

  • Tracing (OpenTelemetry, Jaeger, X-Ray, etc.) — __

Version Control

  • Git fundamentals (branch, merge, rebase, etc.) — __

  • GitHub / GitHub Enterprise — __

  • Branching strategies (trunk-based, Gitflow, etc.) — __

SECTION 8 — Security & Compliance

  • Identity & Access Management — __

  • Secrets management (Secrets Manager, Key Vault, Vault, etc.) — __

  • Zero Trust concepts — __

  • OWASP Top 10 — __

  • Security scanning (SAST, DAST, SCA) — __

  • Network segmentation & least privilege — __

  • Compliance awareness (SOC 2, PCI, HIPAA, etc., as relevant) — __

SECTION 9 — Architecture & System Design

  • Distributed systems design — __

  • Event-driven architecture — __

  • Microservices — __

  • Message queues (Kafka, SQS, RabbitMQ, Service Bus) — __

  • API design (REST, GraphQL, gRPC) — __

  • Performance tuning & profiling — __

  • High availability & failover — __

  • Scalability patterns (caching, sharding, partitioning) — __

  • Resilience patterns (circuit breakers, retries, backoff) — __

SECTION 10 — Tooling & Productivity

  • Markdown authoring — __

  • Vim / NeoVim — __

  • VS Code — __

  • IDEs (Rider, IntelliJ, Visual Studio, etc.) — __

  • Command-line fluency — __

  • Container debugging tools (kubectl, docker exec/logs, etc.) — __

  • Task automation (Make, npm scripts, custom CLIs, etc.) — __

SECTION 11 — AI/ML & Modern Engineering

  • Prompt engineering for LLMs — __

  • Using AI in code generation (Copilot, ChatGPT, Claude, etc.) — __

  • Embeddings / vector stores — __

  • RAG (Retrieval-Augmented Generation) architectures — __

  • LLM “agents” / tools orchestration — __

  • Model hosting / serving — __

  • Basic ML concepts (regression, classification, overfitting, etc.) — __

SECTION 12 — Leadership & Collaboration Skills

Engineering Leadership

  • Mentoring / coaching engineers — __

  • Running effective code reviews — __

  • Providing architectural guidance — __

  • Incident response & postmortems — __

  • Prioritization and trade-off decisions — __

Collaboration & Communication

  • Cross-team communication — __

  • Technical writing & documentation — __

  • Requirements gathering & refinement — __

  • Working with Product / DPM / BA partners — __

  • Facilitating meetings (standups, retros, design sessions) — __

SECTION 13 — Goals & Notes

Technologies you would like to grow in (next 12 months):
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Technologies you would prefer not to own going forward:
__________________________________________________________________
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Career/skill aspirations for the next 12–24 months:
__________________________________________________________________
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