How to become a Full-Stack Data Engineer

How to become a Full-Stack Data Engineer

You must have heard about Full-Stack software developers. There is another stream evolving around the data landscape, named Full-Stack Data Engineer. Basically, who can deal with an end-to-end data ecosystem, from data profiling, and analysis to building an enterprise-level data platform.

Let’s discuss key skills required to become Full-Stake Data Engineer.

1) SQL - It sits in the core, want to do anything with data like Data analysis, Profiling, Data Quality checks, etc.

2) Databases - Proficiency with at least one RDBMS such as Oracle, MySql, Postgres is must-have. Also understanding modern-day cloud data platforms like Redshift, Snowflake is added advantage.

3) ETL - Data Engineers spend most of the time developing ETL (Extract Transform Load) packages. Understanding of ETL and Data warehousing concepts along with hands-on experience of at least one ETL tool like Informatica, Talend, and Matillion is a must.

4) Python/Spark - Dealing with the verity and volume of data like it becomes essential to develop an understanding of any scripting such as Python/Spark adds flavor. Using these along with the power of the cloud opens up opportunities to build highly scalable and available data platforms.

5) Visualization - "Visualization is the language data speaks". Organizations will only be able to rip the benefits of data platforms using proper visualization/reporting. It helps find patterns, get hidden information, and thus taking business decisions.

6) Orchestration - For proper functioning of all these components we need some technology or tools where dependency, schedules, and steps can be configured. Such as Airflow, crontab

7) Cloud technologies - For modern-day storage, compute, serverless, and orchestration needs one must be aware of services offered by cloud platforms such as AWS, Azure, and GCP. It helps to choose the right technology for your use case.

I would encourage budding data enthusiasts to understand these terms and try to evaluate how you are using these in the current setup. Feel free to DM me in case you want to dig deeper or evaluate any use cases.

Happy Learning !!!

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