Job Roles of Data Professionals

In the age of AI, data is more critical than ever, but how is the data profession evolving? In this episode of TrendWatch, Seth Robinson dives into the job roles and skills shaping the data domain, drawing inspiration from a recent article on the rise of the data generalist.

The answer to whether companies need generalists or specialists largely depends on company size. Large enterprises often hire specialists for niche aspects, while smaller businesses typically require a data generalist to handle diverse responsibilities.

CompTIA has defined a taxonomy of five distinct data job roles across two pathways:

1. Data Management Pathway

Database Administrator (DBA): Manages data structures and databases (traditionally structured, now including unstructured data).

Data Engineer: Manipulates and moves stored data toward analysis (e.g., ETL, data pipelines, cleaning) to get it ready for analysis.

Data Architect: Defines the overall data strategy, classification, and how data relates to business decisions.

2. Data Analytics Pathway

Data Analyst: Analyzes various data types to learn from the past and predict the future—a popular and high-demand role.

Data Scientist: An advanced role that builds statistical models, often using machine learning and AI algorithms to go beyond simple pattern recognition.

There is significant opportunity in data—not just for analysis, but also for preparing and training AI systems. As companies increasingly invest in AI outcomes, foundational data skills become essential.

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