7 IT Roles to Help Your Big Data Capabilities

In our data-driven world, the way organizations centralize and harness their data can be a competitive advantage. However, in recent years, the vast volume and variety of data being collected with incredible velocity is being referred to as big data—and the amount of big data is growing exponentially.

In 2019, 41 zettabytes of structured and unstructured data were generated globally. By 2023, nearly three times the volume of data was generated worldwide, and that number is expected to double again by 2025.

To keep pace with big data, nearly all (98%) surveyed executives agreed it is somewhat or very important to increase their data analysis and hiring in the next one to three years.

Let’s look at how big data is impacting business hiring and which data big roles will help organizations navigate this new normal.

What Is Big Data and How Is it Impacting IT Teams?

Before jumping into roles that support big data, it’s helpful to define what it is.

Big data refers to the structured, semi-structured, and unstructured data generated by organizations. Big data is largely defined by the “three Vs”:

  • Volume: Large quantity of data or data sets.
  • Variety: Data from a multitude of sources, including numbers, text, images, videos, and audio.
  • Velocity: The speed with which data is processed, analyzed, and stored.

Big data is generated any time we conduct a search engine query, open an app, or run a report. As organizations generate larger quantities of big data, traditional data tools are no longer equipped to handle the volume or complexity of the data. This gives way to specialized big data software solutions and roles to manage these massive data sets.

7 IT Roles to Help Companies Expand Their Big Data Capabilities

As organizations continue to leverage big data for insights and innovation, there’s a growing demand for IT roles that can support and drive these initiatives. Here are seven IT roles that can help organizations build out their big data capabilities and prepare for the future of big data innovation!

1. Data Scientists and Analysts

Data scientists play a critical role in helping companies parse through and extract meaningful insights from their large data sets. Using machine learning, predictive models, and statistical analysis, data scientists are able to provide actionable insights that support decision-making.

Data scientists should be one of the key roles organizations hire for when building out their big capabilities because of the competitive edge they offer. Using tools like Tableau, Power BI, or Excel, data scientists can harness big data for organizational growth by:

  • Collaborating with business stakeholders to create a comprehensive data strategy
  • Conducting data exploration and analysis to uncover patterns, trends, and insights
  • Building predictive modeling to forecast trends and outcomes
  • Establishing data governance frameworks to protect the integrity and security of big data
  • Applying advanced statistical analysis to derive insights from complex data sets

2. (Big) Data Architect

Big data architects are another key role to hire for, especially as organizations are looking to design their big data infrastructure. Big data architects help plan and implement the systems, processes, and infrastructure needed to handle large volumes of diverse data so they can harness it for insights.

With a big data architect in-house, organizations can design scalable and efficient big data models using the technologies and frameworks that work best for them. These experts should have several years of big data experience and be familiar with Hadoop or other frameworks to help organizations integrate data from various sources and implement data storage solutions to accommodate structured and unstructured data.

3. Big Data or Machine Learning Engineer

Similar to big data architects, big data or machine learning engineers, are instrumental roles for organizations interested in harnessing and controlling their big data capabilities. Big data engineers help to not only design, but also maintain and support the infrastructure needed to process, store, and analyze big data.

Big data engineers support organizations embrace big data by:

  • Designing big data infrastructure based on the specific needs of an organization
  • Developing data pipelines to ingest and integrate data from databases, logs, and external APIs
  • Selecting appropriate storage solutions such as NoSQL databases or data lakes
  • Implementing ETL (extract, transform, load) processes to prepare data for analysis
  • Optimizing the performance of big data

4. Data Quality Analyst

Data quality analysts are becoming a more common role for organizations to hire. As companies collect larger amounts of data, it’s crucial to have individuals on hand who can ensure the data is accurate, reliable, and up to compliance/quality standards.

Data quality analysts help conduct data profiling to understand the quality and structure of data within large systems to identify anomalies, inconsistencies, or potential issues. They are helpful in establishing data quality standards for organizations and creating processes that uphold those standards, like data cleansing processes, monitoring mechanisms, and conducting root cause analyses.

5. Data Governance Manager

Data governance managers are a critical role to hire in industries where effective management, protection, and utilization of data are necessary.

Most commonly, data governance managers are needed in industries that handle large volumes of sensitive information or face regulatory compliance requirements, such as healthcare, finance/banking, insurance, and government/public sector.

Data governance managers help companies develop standards for data quality, security, and lifecycle management to ensure they align with business goals and regulatory requirements. It’s common for data governance managers to define data ownership and implement metadata management processes as part of a larger data quality framework.

6. Data Privacy Officer

Similarly, data privacy officers (DPOs) are essential in ensuring that the organization complies with data protection regulations and policies, like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), while still deriving value from data.

DPOs are helpful roles to have in-house because they help organizations expand their big data capabilities while ensuring compliance with data protection laws.

DPOs advocate for privacy principles and build them into big data design. They are also helpful in conducting privacy risk assessments for big data projects to provide guidance on navigating complex legal frameworks related to data privacy.

7. Chief Data Officer

When organizations are ready to make big data a cornerstone of their IT strategy, it’s time to hire a Chief Data Officer (CDO). The CDO is responsible for the overall data strategy of an organization, ensuring data is treated as a valuable asset and driving data-driven decision-making.

As more organizations embrace big data, there is a growing need for CDOs. In fact, 83% of surveyed senior data executives said their company had an appointed CDO or related role. Even more telling, 92% of data leaders agreed that CDOs helped their company deliver measurable value from data and analytics investments.

Hire Your Next Big Data Role with Insight Global

Regardless of where you are in your big data journey, there are roles to help you embrace and harness the power of your data sets.

Consider working with Insight Global as your trusted partner in big data and IT staffing! Along with our Evergreen managed services division, we can work with you to determine the best strategy for your operations, and we can help you find and hire the talent you need.