By Prangya Pandab - November 09, 2022 4 Mins Read
The Great Resignation makes it challenging for many companies to navigate data management and retain employees with data-related skills. These businesses can benefit from using tools like data observability to retain their data scientists and engineers.
The Great Resignation, as many are aware, had a significant impact on the technology industry. With increasingly complex systems and high business expectations, most data engineers and executives are overwhelmed with developing and maintaining enterprise data systems. Many businesses are having trouble keeping up with data management due to a lack of employees with key data-related capabilities. In order to address this issue, companies must figure out how to manage the constant risk of employee attrition and the ensuing hiring difficulties associated with retaining a skilled workforce capable of creating and managing complex data environments.
Companies need to be aware of the reasons data engineers are departing in droves and focus on fixing that issue if they hope to stop even more from leaving. Employees lack professional growth opportunities in addition to still emotionally healing from the COVID-19 pandemic, which drives them to look for new opportunities to advance their careers. Employers with a strong professional development focus typically have higher retention and engagement rates.
Businesses that invest more time in assisting their data engineers with their professional growth will discover that their employees stay with them longer and are more invested in the company as a whole.
The fact that their role does not correspond with the position for which they were employed is another reason data scientists often quit. People in this situation discover that they spend too much time identifying and fixing errors. They also find that they are exerting excessive effort to handle many stakeholder demands and maintain the data pipeline.
In some cases, the current data governance standards of a company may make it difficult and unpleasant for data engineers to do their work and provide limited opportunities for tasks with high value. Instead, many data engineers spend their time manually fixing errors and ensuring that systems don’t malfunction. These data engineers might have more opportunities for innovation and spend less time simply carrying out operational tasks that only get them to the next interruption with better data observability.
Data observability technology can be used to automate manual data operations within an organization, saving time and opening up new avenues for innovation. Data engineers don’t have to spend their time manually verifying these processes. AI and ML provide comprehensive insight into an organization’s data, making it essential to maintain data amid the great resignation and offer current employees a much-needed break from time-consuming and tedious tasks.
Modern data science platforms can help free up a significant amount of employee time for businesses that invest in them to support their data scientists. Data scientists can concentrate on more significant issues while getting a thorough understanding of data, processing, and pipelines at every stage and point in the data lifecycle rather than wasting their time fighting fires and resolving urgent data concerns.
Data observability enables data scientists to operate at a pace that fosters innovation, flexibility, and creativity—aspects that can all help them avoid burnout and broaden their own skill sets.
Enterprises must identify the reasons why people are leaving their own organization in order to retain data scientists. Many data engineers believe they are underpaid, have few possibilities for career advancement, and struggle to maintain a good work-life balance. It is essential to foster an atmosphere where data engineers feel valued for their hard work.
While organizational culture changes take time to develop, it is crucial to assist the data scientists who are currently employed to prevent further increases in resignation rates. Organizations should look at investing in data observability technology as a reliable way to free up valuable employee time, letting them work on projects that are more closely aligned to their roles and have time for professional development. This will help data scientists feel supported during a staffing shortage.
Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.
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