Upskilling Your Developers Remotely

Remote working was adopted early by the tech industry, and is becoming increasingly popular across all sectors. Hiring remote workers means a broader talent pool and an ability to be more competitive in the eyes of top developers.

However, remote developers can miss out on skills that those in the office might pick up naturally. And in the face of a widening skills gap, upskilling and training is becoming increasingly important.

So how can you ensure you keep your remote workers up-to-date with the latest skills?

Create a learning culture

Learning is an integral part of a Developers career trajectory. According to one survey, almost 90% of developers say that they’ve taught themselves a new coding language without taking a formal course. Spending their own time learning new skills necessary to do their jobs.

As an employer you need to ensure remote workers are encouraged to spend their time upskilling and measure this time as a positive step towards their business goals.

Build a community

From our own experiences working with Developers, we know that many place enormous value on community. The sustained popularity of sites like Stack Overflow shows developers’ openness and willingness to be supportive. Over 70% of software developers feel a sense of connection with their peers. Which is, of course, vital when working remotely.

Businesses can leverage this desire for collaboration by providing access to internal or external communities. Platforms such as Slack allow remote workers to freely engage, ask questions, exchange information, and bond over shared experiences with their coworkers.

Set goals

When it comes to training and upskilling developers, every team member has a different skill set and training need. This means employers must establish individual plans for each remote worker allowing every individual to reach their highest potential.

However, it’s crucial to leave as much freedom to your employees as possible. Most people prefer to learn on their own terms, so it may be counterproductive to impose a certain training/learning plan. It’s also important to think about training that will be beneficial to your company’s overall growth.

Relinquish control

There are many options for training and learning, including less traditional methods such as, bootcamps, hackathons and online coding competitions. It’s important to give your employees the a degree of choice when it comes to learning.

Although some methods may appear ‘non-traditional’, giving your developers the opportunity to choose how they learn will make them feel appreciated and will build trust. This will also lead to increased productivity and a healthier, more successful working culture.

Equipping employees with cutting-edge skills will keep them happy and impact your company’s bottom line. Tech has always led the way when it comes to effectively implementing remote working.

And as the modern workplace evolves, other businesses need to step up in order to stay relevant and attract top talent. Accepting remote working as a positive is most certainly part of this.

Are you looking for talented tech professionals to join your team?  Speak with our specialist consultants today to hear about the hottest talent.

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Benjamin Hanrieder

Q&A Benjamin Hanrieder (CTO, Engel & Volkers)

In this interview, Benjamin Hanrieder, CTO at Engel & Völkers Technology, discusses the company’s digital transformation, software development practices, and the role of the Cloud Platform Team in ensuring reliable and secure infrastructure. Mat Roche (MR): Can you give us an overview of your background?  Benjamin Hanrieder (BH):  Hi Mat,

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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