Habits for success as a Salesforce Technical Architect

A CTA is someone who demonstrates the knowledge, skills, and capabilities to design and build high-performance technical solutions on the Salesforce Platform across all domains.

To be a Technical Architect, you need to be both a big-picture thinker and in-depth problem solver, your knowledge and skills being both broad and deep. This Global Master Instructor at Salesforce shares his habits for developing an Architect mindset, which you can practice on your journey to becoming a CTA.

Engage the community

Answer a technical question, post your own, share useful resources you have discovered (or created), or encourage someone to take the next step in their journey. But most of all, be part of the conversation. The more you engage with the community, the more you’ll get out of it.

Fast thinking

The invaluable Salesforce Architect Trailmixes are a great place to start building these fundamentals.

Brush up on your presenting skills

Use your peers, colleagues and community groups and events to learn more and discover best practices and tips and tricks. 

Give back

Regardless of your job title or role, and as you develop your Architect mindset by practicing these seven habits, give back and share! Why not start today? If you’re interested in getting involved in our Salesforce Q&A series, contact us today.

 

Are you a Salesforce professional looking for your next dream role? Speak with our specialist consultants to hear about the hottest jobs in the market right now.

 

socurce: https://medium.com/trailhead/develop-a-technical-architect-mindset-c0b6c6001fd6

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Seniority

Software Developers
Senior Engineers
Software Architects
Senior Software Architects
Software Tech Leads
Senior Software Tech Leads
Software Tech Lead Managers
Senior Software Tech Lead Managers
Director of Engineering
VP of Engineering


Software Developers
Senior Engineers
Software Architects
Senior Software Architects
Software Tech Leads
Senior Software Tech Leads
Software Tech Lead Managers
Senior Software Tech Lead Managers
Director of Engineering
VP of Engineering

 

Software Developers
Senior Engineers
Software Architects
Senior Software Architects
Software Tech Leads
Senior Software Tech Leads
Software Tech Lead Managers
Senior Software Tech Lead Managers
Director of Engineering
VP of Engineering

 

Role

Full-stack Developers
Back-end Developers
Front-end Developers
DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineer
Security Engineers
Mobile Developers
App Developers
No1 software engineers

Full-stack Developers
Back-end Developers
Front-end Developers
DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineer
Security Engineers
Mobile Developers
App Developers
No1 software engineers

Full-stack Developers
Back-end Developers
Front-end Developers
DevOps Engineers
SRE Engineers
Cloud Engineers
Platform Engineer
Security Engineers
Mobile Developers
App Developers
No1 software engineers

Skills

React.js
Node.js
AWS
JavaScript
React
Native
PostgreSQL
Ruby on Rails
Java
Angular
Golang
PHP

React.js
Node.js
AWS
JavaScript
React
Native
PostgreSQL
Ruby on Rails
Java
Angular
Golang
PHP

React.js
Node.js
AWS
JavaScript
React
Native
PostgreSQL
Ruby on Rails
Java
Angular
Golang
PHP

Sample By Job Family

Data Scientists
Data Engineers
Data Architects
Data Modelers
BI Developers
Data Analysts
Data Quality Engineers
Data Governance Experts MLOps Engineers
DataOps Engineers
Data Product Managers
Executive Data Leadership

Data Scientists
Data Engineers
Data Architects
Data Modelers
BI Developers
Data Analysts
Data Quality Engineers
Data Governance Experts MLOps Engineers
DataOps Engineers
Data Product Managers
Executive Data Leadership

Sample of Platforms & Tools

Cloud DW: Snowflake, BigQuery, Redshift ETL/ELT Tools: Airflow, dbt, Fivetran, Talend Big Data Frameworks: Spark, Hadoop, Kafka BI & Visualization: Tableau, Power BI, Looker ML Libraries: TensorFlow, PyTorch, Scikit MLOps Platforms: MLflow, Kubeflow, W&B Data Governance: Collibra, Alation Data Observability: Monte Carlo, Databand Data Lakes: Lake Formation, Delta Lake SQL/NoSQL DBs: PostgreSQL, MongoDB Real-time Analytics DBs: Apache Pinot, Druid Gen

Cloud DW: Snowflake, BigQuery, Redshift ETL/ELT Tools: Airflow, dbt, Fivetran, Talend Big Data Frameworks: Spark, Hadoop, Kafka BI & Visualization: Tableau, Power BI, Looker ML Libraries: TensorFlow, PyTorch, Scikit MLOps Platforms: MLflow, Kubeflow, W&B Data Governance: Collibra, Alation Data Observability: Monte Carlo, Databand Data Lakes: Lake Formation, Delta Lake SQL/NoSQL DBs: PostgreSQL, MongoDB Real-time Analytics DBs: Apache Pinot, Druid Gen

Sample of Skills Delivered

Programming in Python, R, and SQL
Python
Data Modeling Statistical
Analysis ETL/ELT
Pipeline Development
Database Design & Administration
Machine Learning Fundamentals
Cloud Data Warehousing
Data Ethics & Compliance
Data Security
Data Visualization & Storytelling
Real-Time Data Streaming

Programming in Python, R, and SQL
Python
Data Modeling Statistical
Analysis ETL/ELT
Pipeline Development
Database Design & Administration
Machine Learning Fundamentals
Cloud Data Warehousing
Data Ethics & Compliance
Data Security
Data Visualization & Storytelling
Real-Time Data Streaming

Sample By Job Family

AI Software Engineers
Gen AI Engineers
Machine Learning Engineers
Deep Learning Engineers
Prompt Engineers
AI Research Scientists
NLP Engineers
Computer Vision Engineers
MLOps Engineers
AI Product Managers
AI Governance Specialists
AI Ethics Office
AI Architects Executive

AI Software Engineers
Gen AI Engineers
Machine Learning Engineers
Deep Learning Engineers
Prompt Engineers
AI Research Scientists
NLP Engineers
Computer Vision Engineers
MLOps Engineers
AI Product Managers
AI Governance Specialists
AI Ethics Office
AI Architects Executive

Sample of Platforms & Tools

LLMs: Open AI, Anthropic, Llama, Gemini ML Platforms: SageMaker, Vertex AI, Azure ML ML Libraries: scikit-learn, XGBoost, LightGBM DL Frameworks: TensorFlow, PyTorch, Keras LLM Frameworks: LangChain, LlamaIndex Vector Databases: Pinecone, Weaviate, Milvus Data Science Notebooks: Jupyter, Colab, Kaggle Data Visualization Libraries: Matplotlib, Seaborn NLP Libraries: Hugging Face Transformers CV Libraries: OpenCV, Pillow, Albumentations MLOps Tools: MLflow, Kubeflow, W&B

LLMs: Open AI, Anthropic, Llama, Gemini ML Platforms: SageMaker, Vertex AI, Azure ML ML Libraries: scikit-learn, XGBoost, LightGBM DL Frameworks: TensorFlow, PyTorch, Keras LLM Frameworks: LangChain, LlamaIndex Vector Databases: Pinecone, Weaviate, Milvus Data Science Notebooks: Jupyter, Colab, Kaggle Data Visualization Libraries: Matplotlib, Seaborn NLP Libraries: Hugging Face Transformers CV Libraries: OpenCV, Pillow, Albumentations MLOps Tools: MLflow, Kubeflow, W&B

Sample of Skills Delivered

Generative AI Development
Machine Learning Algorithms
Deep Learning Architectures
NLP and NLG
Computer Vision
Data & Feature Engineering
MLOps & Model Deployment
Statistical Analysis & Hypothesis Testing
Python and R Programming Expertise
Model Evaluation & Performance Tuning
AI Governance & Compliance
Autonomous AI Agent Engineering
Building Agentic AI Applications

Generative AI Development
Machine Learning Algorithms
Deep Learning Architectures
NLP and NLG
Computer Vision
Data & Feature Engineering
MLOps & Model Deployment
Statistical Analysis & Hypothesis Testing
Python and R Programming Expertise
Model Evaluation & Performance Tuning
AI Governance & Compliance
Autonomous AI Agent Engineering
Building Agentic AI Applications