Data engineers, the unsung heroes of data science

Joshua Carter our consultant managing the role
Posting date: 5/21/2018 6:33 PM
Before you can build a house, you need a blueprint of its design and schematics. When you begin construction, you must first lay the foundation upon which it will be built. Tangible products taken step-by-step to create first a house and then a home. However, in the world of data science, companies seem to have skipped the blueprints and foundational aspects and gone straight for the aesthetics. But, how do you decorate a house before it’s built?

A house without a foundation becomes a house of cards and the same is true of data analysis. Before the data scientists can process and analyse data, first must come the engineers. The Data Engineers who lay the digital foundation and set the parameters, who create the data lakes and platforms, so the data analysts have something to make sense of. As high as the demand is for data scientists, the demand and the need, is even greater for data engineers, yet a shortage remains.


Where are the Data Engineers?

Data engineering jobs outnumber data scientist jobs nearly four to one according to a quick search on job boards such as Glassdoor and Indeed. Yet, the complex technical nature of data engineering to support data scientists takes more than a degreed education. Unlike data analysts, data scientists, and other data professionals who can land a mid-level job directly out of university, data engineers cannot.

Ultimately, it takes between five to ten years for mid-level data engineers to gain enough experience for practical application. As such, systems do not yet exist in schools and universities to supplement data engineers undergraduate or postgraduate degrees in preparation for real life work experience in the field. However, once the experience is gained, it can take a company who has hired a data engineer up to two years to catch up with its competition.

With the pace of change in the tech world, this can be detrimental to both the business and the data science teams. Therein lies the Catch-22, data engineers must have experience before they can be hired, but there is no way to learn outside of hands-on, real life application.


Why You Need to Add a Data Engineer to Your Data Science Team

A data science team is not complete without a data engineer. Why? Because just like building a house, grand schemes and ideas to solve complex business problems, must first have a foundation. Data engineers are that foundational support of experts who design, build, and maintain data-based systems and organizational operations.

Not only do data engineers lay the foundation upon which data can be built, analysed, and ultimately translated to business professionals, it must also be timely.  Timely data leads to more data and better predictions.

Data engineers are not completely siloed from data science teams, they are also responsible for deploying the code and models that are written by data scientists. For more on the reasons data engineering is more important than data science for companies today, check out this article from Captech Consulting.

Data Science Team Seeks Data Engineer

Companies know data drives business and they know the importance of data professionals. However, they may mistakenly assume either that their data teams can pick up engineering experience as they work their way through a project or they simply assume the titles are interchangeable.

In the world of data engineering, there is no entry level job. Experience trumps education in this field.

Like the once siloed data science team now integrated across the business with sales, marketing, and advertising departments, so must the role of data engineer be integrated. This is not a marriage of convenience, but of necessity in order to stay ahead of the competition. Together, your fully integrated data teams – data engineering and data science now on equal footing - will be able to help your business reach better predictions faster, making you a voice of authority in your discipline.

Your Turn: Route to the Role of Data Engineer

The route to the role of Data Engineer may seem daunting with the catch-22 that experience supersedes education. So, in the spirit of collaboration, we thought we’d ask for your thoughts and opinions on a few items of interest such as how we can educate aspiring data engineers and get them into companies faster. What kind of cross-training programs might businesses and schools employ to fill the shortage? What other backgrounds are we overlooking as businesses seek to find and engage this most critical role within their data science teams?

According to the website Datanami, 2018 will be the year of the data engineer. If this is you, then we may have a role for you.

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MeasureCamp Berlin

MeasureCamp Berlin: A Preview

In preparation for this year's MeasureCamp Berlin, we sat down with Benjamin Bock, communications lead, to discuss what to expect, as well as his thoughts on the industry in general. Here's what he had to say: Can you explain MeasureCamp for people who haven’t been yet? MeasureCamp is an open, free-to-attend analytics 'un-conference' made by analytics professionals for analytics professionals (and everyone who wants to get there) around the globe. In that sense, it’s different to any conference you know of. Our schedule is created on the day of the event, and our speakers are fellow attendees. Listen to talks, give a talk, and discuss topics that really tickle your fancy. What can we expect at MeasureCamp Berlin this year? Let’s begin with what you can’t and never will expect at MeasureCamp Berlin: Sales pitch presentations. We’ve all been there… you are visiting a fancy, expensive conference and all you get is Heads of 'This n’ That' talking about what their team did, what they spent money on and that you should buy Product X to be as Data-driven as them (mind the cynicism). At MeasureCamp you can expect talks and discussion rounds by around 150 fellow experts, who all know the daily adventures of cleaning Data, setting up analytics or debugging tracking code or running mind-bending analysis first hand.  What is your best tip for someone that has never been at MeasureCamp before? Don’t rush it! MeasureCamp is about mingling with the analytics community as much as it is about the talks and discussion rounds. Pick a few talks that really interest you and use the rest of the day to get to know other attendees. Our awesome sponsors are also more than happy to talk to you. What is the best advice you got last year at MeasureCamp? On a personal level, I was able to get some really good advice when it came to data privacy topics. GDPR was still fairly fresh and nobody really knew if what they had done was actually enough to not get into trouble. That’s the kind of advice you only get if you have the chance to talk to other professionals face to face. On another note, what are the most sought-after skills and technologies currently used? I can only speak of my experience here. On a hard skill level and depending on the individual role, you need a solid understanding of web technologies (JavaScript, HTML, CSS) and tag managing systems to be able to implement tracking (plus some knowledge in mobile development when your focus lies on apps). When it comes to analysing and visualising Data, you should understand the tool you are working with and its underlying Data-structures. Being able to retrieve tool-agnostic Data with SQL and running more sophisticated calculations (e.g. with Python) has become more and more important over the last few years. But there are some softer skills, that should not be overlooked as well. As an analytics professional, you should never assume that your knowledge and language are common ground. You need to be a strong communicator, who is able to explain complicated concepts broken down to the absolute basics. In your opinion, what will be the biggest challenge in digital analytics in the next year? Two weeks ago, I would have answered “bringing web and app Data together”. Now that we know Google is working on that topic, it’s still a challenge, but one I am happy to tackle in the coming year. Digital Analytics is constantly changing. What do you expect to be the most talked about topic at MeasureCamp this year? As a Tracking Specialist with a focus on Google products, I’d love to hear some talks about Google Tag Manager Custom Templates. But my top guess is, that the newly released Apps and Web properties beta for Google Analytics will be the talk of the hour. MeasureCamp Berlin is an open and free-to-attend 'un-conference', taking place this year on the 28th of September. The final batch of tickets will be released on the 21st of August at 03:00 PM (CEST). Click here for more information and to get hold of your place. 

Where Tech Meets Tradition

Where Tech Meets Tradition

If you’re lamenting the decline of handmade traditional products, cast your cares aside. There’s a new Sheriff in town and its name is, Tech. Just a generation ago, children would leave the farm or the family business, go to school, and then move on to make their place in the world doing their own thing. Away from family.  Today, the landscape has changed and those who have left are coming home. But this time, they’re bringing technology with them to help make things more efficient and more productive. Is Tech-Assisted Still Handmade? In a word, yes. Artists still make things “from scratch”, except now technologies allow them to not only see their vision in real-time, but their customers, too. Have you ever wondered what the image in your head might look like on paper or in metal? What about the design of prosthetic arms and healthcare devices by 3D printers? You’re still designing, creating.  But just like any new technology, there’s still a learning curve. Even for cutting-edge craftspeople who find that sometimes, the line between craftsmanship and high-tech creativity may be a bit of a blur. Not to mention the expense for either the equipment required or being able to offer art using traditional tools at technology-assisted prices. Somewhere between the two, there is a trade-off. It’s up to the individual to determine where and what that trade-off is. Life in the Creative Economy One of Banksy’s paintings shredded itself upon purchase at an auction recently. AI is making music and writing books. Augmented Reality, Virtual Reality, and Blockchain all have their place in the creative economy from immersive entertainment to efficient manufacturing processes. Each of these touches the way we live now. In a joint study between McKinsey and the World Economic Forum, 'Creative Disruption: The impact of emerging technologies on the creative economy', the organisations broke down the various technologies used in the creative economy and how they’re driving change. For example: AI is being used to distill user preferences when it comes to curating movies and music. The Associated Press has used AI to free up reporters’ time and the Washington Post has created a tool to help it generate up to 70 articles a month, many stories of which they wouldn’t have otherwise dedicated staff.Machine Learning has begun to create original content. Virtual Reality and Augmented Reality have come together as a new medium to help move people to get up, get active, and go play whether it’s a stroll through a virtual art gallery or watching your children play at the playground.  Where else might immersive media play out? Content today could help tell humanitarian stories or offer work-place diversity training. But back to the artisan handicrafts.  Artistry with technology Whilst publishing firms may be looking to use AI to redefine the creative economy, they are not alone. Other artists utilising these technologies include:  SculptorsDigital artistsPaintersJewellery makersBourbon distillers America’s oldest distiller has gotten on the technology bandwagon and while there is no rushing good Bourbon, but you can manage the process more efficiently. They’ve even taken things a step further and have created an app for aficionados to follow along in the process. Talk about crafted and curated for individual tastes and transparency. It may seem almost self-explanatory to note how other artisans are using technology. But what about distilleries? What are they doing? They’re creating efficiency by: Adding IoT sensors for Data Analytics collection Adding RFID tags to their barrels Creating experimental ageing warehouses (AR, anyone?) to refine their craft. Don’t worry, though. These changes won’t affect the spirit itself. After all, according to Mr. Wheatley, Master Distiller, “There’s no way to cheat mother nature or father time.” Ultimately, the idea is to not only understand the history behind the process, but to make it more efficient and repeatable. A way to preserve the processes of the past while using the advances of the present with an eye to the future. If you’re interested in using Data & Analytics to drive creativity, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expect consultants to find out more. 

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