Read on to know how you can be in line for hottest job of the future.
If the topic of this article interests you, then chances are that you’re looking into Big Data as a career. As the market of Big Data is rapidly evolving, where you end up in it is largely dependent on your first step.
Luckily for you, we’re going to start from scratch and give you both the big picture and the microscopic details of pursuing the career of a Big Data Architect.
Before diving in further let’s get a peak at what’ll get covered in the article.
For Those Who Came in Late…
Let’s address the elephant in the room: Big Data. People have literally been gaga over it for the past ten years, and everyone who hasn’t been living under a rock in the Himalayas is familiar with the term.
The problem is simple: processing large chunks of data (by large, we mean from a few terabytes to a few petabytes).
|The Job of a Big Data Architect, revolves chiefly around finding a simple, viable, cheap, and effective solution to the problem.|
Before we move on, we’re going to lay down the most fundamental units of big data for you to glaze through. If you haven’t heard of any of them, consider clicking on the links to read about what they are, and be fascinated.
- Hadoop. It’s an ecosystem where most applications that deal with big data run. Big Data without Hadoop is like cricket without a bat. A big data architect’s world, is Hadoop.
- Spark. It’s a platform that can work alone or in conjunction with Hadoop to process data a hundred times faster. Most practical applications of Big Data nowadays use Spark.
- Pig, Hive, Sqoop, Flume, Kafka, Mahout, Drill, and a host of other applications that contribute in one way or another to making data processing simpler, faster, cheaper, or all three. As a beginner, you should at least have a vague idea of what they do.
Phew! Now that that’s out of the way, let’s jump directly to all about Big Data Architects!
Who is a Big Data Architect?
In computer science “architecture” is building computer systems. The “systems” can be large and intricate, and to keep them working, you need a list of rules and methods that have to be followed.
|An “Architect” is then, the person who comes up with these rules and methods and incorporates them into the building of a computer system.|
If the computer system is being built to process data, then the person is a data architect. And if the system is meant to process “Big Data”… well, make a wild guess.
Are all Big Data Architects the same?
No. Just look at the list of software that we named up there as “starting” material for entering Big Data. No human could possibly have mastery over ALL of it! Luckily, Big Data applications vary widely from organization to organization.
For example, one use case might involve stream processing of petabytes of data on an everyday basis. Another might involve using batches of data for analytics involving machine learning.
Both jobs require Big Data Architects, but what they’ll be doing at the ground level is quite different! Just as in any other disciplines, big data architects acquire specializations in one aspect or another of the discipline as they progress as professionals.
Big Data Architect: A Typical Job Description
As stated above, descriptions of specific jobs for Big Data Architects vary from organization to organization. We went through a whole bunch of them, and sorted out a few generic elements that were common to all of them:
- A big data architect provides a solution. Hence, one of their primary tasks is to collaborate with the people whose problem they’re solving; that is, engineers, data scientists, and product architects.
- Unless the concerned organization is new, big data has to be implemented seamlessly with an already existing framework of data processing. This creates problems for some people, chiefly data scientists, IT support, and management. Once again, it’s up to the big data architect to collaborate and achieve optimal ends.
- Designing and developing big data components. Data components are often a specific and unique combination of big data tools and methodologies. Hundreds of tools and ideas exist out there – the big data architect must pick the most suitable ones.
- Programming. Be it Java, Scala, R, Python, or scripting languages such as UNIX Shell scripts, coding is an integral part of the job.
- The jobs requires the handling of large-scale challenges innovatively and finding the simplest solutions to often complex problems involving the building, automation, augmentation, and troubleshooting of big data systems.
The Necessary Qualifications of a Big Data Architect
We looked long and hard, but there are no “fresher” jobs for Big Data architect (here’s a pat on your back if you’re reading this from your college dorm).
|The qualifications that make a solid CV for a big data architect comes more from experience and technical training than from university (unless, of course, you went to Stanford or Berkeley). Still, as far as education goes, most jobs ask for a “Bachelor’s/Master’s in Computer Science, or equivalent work experience”.|
Here’s a screenshot from a typical job description for Big Data Architect (here’s the source link, but don’t get excited, the position is probably long filled and the link may/may not work).
Job and Salary Trends of Big Data Architect
Big Data architects receive compensations that are at par with the complexity of work that they do. And as the big data industry accelerates to unforeseen horizons, so does the money that comes with it! Just look that this Indeed job trend of Big Data and Data Science.
When compared to other data analytics positions, job that involve Hadoop and frameworks that operate on the Hadoop ecosystem persistently pay a significant notch higher than their counterparts:
When it comes to work sectors the knowledge of Big Data can get you into a wide variety of academic, industrial, and commercial sectors Here’s a pie chart showing the distribution of big data jobs by sector in 2016:
Both these images have been taken from this eBook published by Penn State University. It’s work a scroll through at the very least, if not a read, if you’re interested in Big Data!
Becoming a Big Data Architect: Your Roadmap in 5 Steps
Let’s be quite frank here: the five steps that you have to take is largely dependent on what position you’re in as you read this: These steps apply primarily to professionals who are presently employed in a data science related field and want to escalate their position to encompass Big Data.
- Map out which skills you have and which skills you don’t.
Maybe you’re good at Python but don’t have any experience in Java. Maybe you have workstation level experience in machine learning but do not have any idea how to incorporate it in a cluster. Knowing where you are short allow you to move ahead!
- See if your present job description can be suitably made to accommodate new skills
This is the best case scenario: if a proposal for a new project is up for submission, tailor it to your advantage! Does R offer significant advantages in your current project over C++, which you’re using? See if you can make the switch! Of course, this may not always be possible, but it’s worth looking at.
- If your present job doesn’t allow you to enhance the skills you don’t have, seek professional training and certification. Multiple institutions have sprung up in the last few years that offer highly specialized training both at the basic and advanced levels, and some of them have come to be quite reputable! A certification from these institutions is as good as work experience in the field!
- Get employed as a data scientist or related position in an organization that incorporates big data into its system to gain experience. Working hands on at ground zero is what makes a big data architect worth their capabilities. Besides, you’ll be incredibly lucky to land a job as a big data architect without at least some experience working in a data analytics industry, so go grab a couple of those years!
- Start your career as a big data architect!
To sum up (tl;dr):
- Big Data architects build large computer systems and equip them with the right platforms, rule, and methods to handle big data
- It’s a highly challenging position to hold and requires plenty of experience to get into
- Job descriptions vary widely depending on sector, scale, and requirements, so you can probably get close to the industry you’re passionate about, no matter where you start from.
- It’s one of the highest paying jobs in the IT industry.