Get to the next-level by knowing exactly how AI is changing the game, which tools will turbo charge your output and what companies are best for you
Find the personalized AI tools that make you more productive:
Data Engineer skills
In demand
Machine Learning and AI Integration: Proficiency in deploying and managing machine learning models using TensorFlow, PyTorch, or Scikit-Learn. Experience with model serving platforms like TensorFlow Serving or MLflow.
Big Data Technologies: Expertise in distributed computing frameworks such as Apache Spark and Hadoop. Knowledge of cloud-based big data services like AWS Redshift, Google BigQuery, or Azure Synapse Analytics.
Data Governance and Security: Skills in data governance frameworks and compliance with regulations like GDPR or CCPA. Experience in implementing data security practices and tools such as encryption and access controls.
Data Engineer skills
Out of demand
Data Cleaning and Transformation: Routine tasks like data cleaning and simple transformations are increasingly automated by AI-driven tools, reducing the need for manual scripting and ETL processes.
SQL Query Writing: While SQL remains essential, many basic query tasks are being automated by advanced analytics platforms and natural language query tools, diminishing the demand for manual SQL expertise.
Data Integration: Integrating data from disparate sources using custom code is being supplanted by automated data integration platforms and ETL tools that streamline these processes with minimal human intervention.
Use AI to find out how your skills match up the the changing demands of the AI-driven market:
