Are you attaining your goals?

Blog Summary: (AI Summaries by Summarizes)
  • Reflect on how you did this year before making goals for the next year.
  • Becoming a Data Engineer requires a significant amount of time, effort, and skill.
  • Check if you have achieved your goal of becoming a Data Engineer.
  • If you're not making progress towards your goal, you need more help.
  • Use a proven source of learning to become a Data Engineer.

We’re coming on that time of year when many people make their goals for the next year. Before you do that, reflect on how you did this year. If you accomplished a goal, how did you do it? If you didn’t accomplish a goal, what happened?

Many people wrote in to me with the goal of becoming a Data Engineer. That’s a great goal and one that I’ve help thousands of people attain.

How did you do at this goal? Did you get a job as a Data Engineer? Have you had this goal of becoming a Data Engineer and still not attained it?

I’ve found a wide array of levels of effort in hitting this goal. Some people have spent hours watching YouTube videos. Others have bought an online course that is really introductory. Still others are held up by the programming requirements of Big Data.

This is the point in time where you take a really honest look at the time you’ve spent and see if they’ve actually paid off:

  • Do you have a job as a Data Engineer (this should be your end goal)?
  • Could you pass a Data Engineer interview or would you crash and burn at the whiteboard?
  • Do you understand Big Data concepts or does your lack of understanding show through during an interview?
  • Could you pseudo-code WordCount?
  • Could you pseudo-code finding all the distinct words in a petabyte of data?

If you’re looking at these and saying no; you need more help. If you looking at these questions and saying maybe, you probably won’t pass that interview. If you’re saying yes, I invite you to take out a pen and paper and do the pseudo-coding. These aren’t arbitrary questions; these are the basic questions you’ll see at every Data Engineer interview. You’ll get more complicated questions than this. You need to be ready.

Becoming a Data Engineer isn’t an easy process. It requires a significant amount of time, effort, and skill.

Not attaining your goals happens one day a time. It starts with being disheartened because watching those YouTube videos doesn’t teach you everything you need to know. That online course is too introductory to even pass an entry level Data Engineer interview. You keep spending time and not getting anywhere. You’re not making any progress on the goal you want to achieve so much.

What should you do?

You need to use a proven source of learning to become a Data Engineer. I’ve taught thousands of students at hundreds of companies. I specialize in taking Software Engineers and making them Data Engineers. My curriculum has been proven to take Software Engineers and making them Data Engineers.

If: * You actually want to achieve your goals this time * You’re tired of wasting your time * You’re lost in the maze of Big Data technologies and don’t know which ones are actually used in production

I encourage you to join my list. That’s the only place my Professional Data Engineering course is offered.

My Professional Data Engineering course teaches you the skills you need to become a Data Engineer. Most courses just teach a single technology. That isn’t a Data Engineer; that’s a Software Engineer who knows a little about Big Data. A Data Engineer needs to know many different technologies to use the tool for the job.

The course teaches you how to create data pipelines. That’s the distinguishing factor between a Software Engineer and a Data Engineer. A Data Engineer must know how to create efficient data pipelines and data products using the right technologies for the job.

If you’re failing at interviews or wasting your time on introductory courses, sign up for my email list so that you can join my ranks of successful Data Engineers.

Related Posts

zoomed in line graph photo

Data Teams Survey 2023 Follow-Up

Blog Summary: (AI Summaries by Summarizes)Many companies, regardless of size, are using data mesh as a methodology.Smaller companies may not necessarily need a data mesh

Laptop on a table showing a graph of data

Data Teams Survey 2023 Results

Blog Summary: (AI Summaries by Summarizes)A survey was conducted between January 24, 2023, and February 28, 2023, to gather data for the book “Data Teams”

Black and white photo of three corporate people discussing with a view of the city's buildings

Analysis of Confluent Buying Immerok

Blog Summary: (AI Summaries by Summarizes)Confluent has announced the acquisition of Immerok, which represents a significant shift in strategy for Confluent.The future of primarily ksqlDB

Tall modern buildings with the view of the ocean's horizon

Brief History of Data Engineering

Blog Summary: (AI Summaries by Summarizes)Google created MapReduce and GFS in 2004 for scalable systems.Apache Hadoop was created in 2005 by Doug Cutting based on

Big Data Institute horizontal logo

Independent Anniversary

Blog Summary: (AI Summaries by Summarizes)The author founded Big Data Institute eight years ago as an independent, big data consulting company.Independence allows for an unbiased