Data engineering is a rapidly developing field. Ten years ago, the job of data engineer barely existed at all. However, demand for this type of software developer has increased. Because of the growth of the field, the function expanded with time.
Data engineers have different roles and duties depending on the organization and the field. Cloud computing and software as a service (SaaS) products will be heavily utilized by data engineers in the near future. They will focus on coding and more on monitoring. Also, engineers in charge of data will be reassigned from “feature” teams to “foundation” teams.
Take a look at the details.
Sneak Peek Into The Future Of Data Engineering
- In the future, data engineers will rely heavily on SaaS and cloud services.
- A decade ago, businesses only had access to on-premises infrastructure for data storage. This is why initial big data technologies were designed for in-house deployments. Data engineers back then spent an inordinate amount of time fine-tuning the settings on their computers rather than developing solutions that would benefit their companies.
- As a result, cloud service providers emerged, making good on their promise to supply services they would handle on your behalf. This will allow one to concentrate on the requirements of your organization.
- These days, big data is simple because of cloud services and technology firms. As a result, the data ecosystem as a whole has developed. Specific areas of data such as data governance, data quality, and data ingestion, gave rise to new startup companies. The two items work together without any failure.
- Today’s data engineers evaluate and select appropriate software. They are well-versed in the ecosystem and proficient in conducting benchmarking and selecting appropriate decision criteria.
- It’s not always simple to determine which tool is best for a certain task. However, a unified data platform is difficult to build because of the disparate technologies required to create it. There are data engineers out there who are already using infrastructure as code to put together these pieces and automate deployment.
- There will be a shift in focus from coding to monitoring for data engineers. Data developers no longer appear to be tasked with building elaborate ETL pipelines in Scala and Spark.
- The dbt methodology introduced a new paradigm for data transformation, one in which SQL is used extensively within the data warehouse. Moving away from ETL and into ELT is now finished.
- New data engineers won’t be specializing on any one data product. Their ultimate goal is to increase output within product teams. They will be the ones to supply the necessary equipment for this to happen. Distributed ownership with a core group that supplies all the resources for creating data products.
Roles And Responsibilities
Eventually, data engineers will take on a greater operational focus. Updating the company’s data infrastructure is a top priority for the next generation of data engineers. Their roles and responsibilities will include:
- Keep an eye on how data workflows are being executed and set up alerts in case of problems.
- implementation of data use-case infrastructure
- Put in place CI/CD pipelines to ensure bug-free code and prompt rollouts.
- Always verify data quality
A data engineer’s day-to-day tasks will alter, but their role within the company will also develop over time.
Data Engineering Jobs
Data engineering occupations will continue to be significant in the future. In terms of the number of jobs listed compared to other data-related jobs, data engineering ranks number one with roughly a 50% growth rate. The demand for data engineers has overtaken the supply. The average salary of a data engineer in India is approximately 3-21 lakhs per annum. This makes data engineering one of the highest-paid data-related careers today.
As with any technology-related employment, the skill sets needed for the field of data engineering will definitely grow. Advanced hardware and sophisticated software are bound to affect the way things are done today. Keep up with cutting-edge innovations but never losing sight of the importance of fundamentals like knowing your audience through and out so you can effectively serve them. Gain an expert level understanding of SQL, programming in general (you might start with Python), or a data engineering certification.