Education & Career Trends: October 3, 2024
Curated by the Knowledge Team of ICS Career GPS
- Excerpts are taken from an article published on dataversity.com.
As more organisations become data-driven, the demand for capable data professionals to support and advance their initiatives has never been greater. Employment in computer and IT occupations is expected to grow 15% from 2021 to 2031 – significantly faster than the average for all occupations. Additionally, data-centric roles rank among the best jobs for earning potential, job satisfaction, and availability.
Which direction should you take when building a career in data?
Below, we have highlighted a few top Data Management careers to consider:
Data Architect
- A data architect works with data at the most comprehensive level, translating the organisation’s overall data strategy into an effective data architecture.
- Data architects work with different departments and stakeholders to design and create the enterprise data management framework.
- Data architects’ most popular skill sets include coding languages, SQL, ETL/ELT operations, database work, and data warehousing.
- Data architects must also understand data modelling and have experience with business intelligence work.
Data Analyst
- The data analyst’s job is more about getting data from a repository and putting it to good use – by developing business intelligence or assisting with key business operations.
- Data analysts will typically extract and analyse data using SQL and other tools.
- They might also maintain a database or multiple database structures.
- Because data analysts will often work with raw, unstructured data – which lacks the cohesive elements that make it ready for use – their skills will be partially related to cleaning, extracting and refining data.
- Data visualisation is a key skill for this role, as well as experience with statistics.
Data Manager
- A data manager maintains an organisation’s data according to established policies and procedures.
- Why is this important? So much of the work that is done with data has to conform to a set of policies.
- This helps with compliance with industry or agency standards and can also protect against the high cost of data breaches or data leaks.
- Data managers often catalogue data for the business and work according to a data governance programme.
Data Scientist
- Data scientists tend to focus more on using scientific methods to work with data, whereas data analysts work more on interpreting and presenting it.
- Some of the key responsibilities for data scientists include data mining, using machine learning programs, and working with structured and unstructured data according to certain kinds of data science like classification, linear regression, or even neural network models.
- Data scientists must have programming skills, such as knowledge of Java or C++, and experience with statistics.
- A data scientist is also well positioned if he or she understands key concepts in machine learning algorithms.
Data Governance Lead
- The data governance lead works with data governance across multiple domains, responsible for creating and communicating policies and procedures.
- A data domain is simply a logical grouping of data in some way.
- Different data domains may include architectures that work like silos to isolate key data from other applications.
- Typical data domains include customer data, product data, financial data, or certain kinds of operational data in end-user systems.
- Because data governance leads work across multiple domains, and with multiple departments, they benefit from having leadership skills as well as experience with data privacy rules like CCPA and GDPR.
Data Modeller
- A data modeller works with data models that are streamlined for workflows and operational results, typically focusing on building frameworks for how data moves through a given workflow.
- Data modellers benefit from having data warehousing, communication, and conceptual skills that will help them develop those models.
- Computer science programs can help build this conceptual skill set by having students brainstorm how to code a particular application.
Data Engineer
- A lot of the data engineer’s work will touch on some of the work done by the above roles in analysis, pipeline development, and more.
- A data engineer may be involved in acquiring data sets, achieving compliance, developing algorithms, or building, testing, and maintaining data pipelines. Data engineers may also be involved in validating or analysing data.
- Required skills include coding languages like C++ or Python, experience with relational and non-relational database skills, data storage, and ETL.
- A data engineer who understands machine learning is also important to an organization.
Conclusion
This list of Data Management careers is only the beginning: From data curators to data stewards to data security analysts, there’s no shortage of job roles to pursue. Regardless of the path you take, learning how to use, manage, and make the most of data will position you for success at any data-focused enterprise – both now and in the future.
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(Disclaimer: The opinions expressed in the article mentioned above are those of the author(s). They do not purport to reflect the opinions or views of ICS Career GPS or its staff.)
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