If it seems the Data world is drilling down further into niche specialities, you’re right. Considering the swathes of information sent and received on a day-by-day, minute-by-minute, and second-by-second basis, is it any wonder? The sheer volume, depending on your business and what you want to know, requires not just a Data team, but must now include someone with a particular skillset, including the tech-savvy analyst who can speak to the executive team.So, who holds it all together? These swathes of information. Who organizes the information in a cohesive order, so anyone with a map, can make their own analyses? Enter the Analytics Engineer.What Makes an Analytics Engineer an Analytics Engineer?Though it’s a rather new speciality within the Data Scientist scope—think Machine Learning Engineer, Software Engineer, Business Analyst, etc—at its core, the definition of an Analytics Engineer is this: “The analytics engineer sits at the intersection of the skill sets of data scientists, analysts, and data engineers. They bring a formal and rigorous software engineering practice to the efforts of analysts and data scientists, and they bring an analytical and business-outcomes mindset to the efforts of data engineering.” Michael Kaminsky, consultant, and former Director of Analytics at Harry’s.In other words, analytics engineers, using best software engineering practices transform data through testing and documentation so that data analysts begin with cleaner data to analyze. As technically savvy as the engineer must be, they must also be able to explain to stakeholders what they’re looking at so they can formulate their own insights. Five Roles and Responsibilities of the Analytics EngineerLike all new niche specialities, there are core responsibilities to consider as well as that of skillsets required to either study to become an Analytics Engineer or to discover if you’re one already. How? Consider the questions you ask, your studies within Data Science, Computer Science, Statistics, and Math, and your balance between technical skills and soft skills. Below are five things to consider when thinking about this role:Programming language experience. Experience with programming languages like R and Python along with strong SQL skills which are at the core of this role.  DBT technology knowledge. As the driving force behind the rise of Analytics Engineer as a separate role, it’s imperative anyone interested in pursuing it should have a firm grasp of DBT — the Data Build Tool — that allows the implementation of analytics code using SQL. Data tracking expertise using Git. Data modelling. Clean, tested, and raw data which allow executives and analysts to view their Data, understand it within the database or its warehouse. Data transformation. Analytics Engineers determine what Data is most useful and transform it to ensure it fits related tasks. It’s part of building the foundational layer so businesses can answer their own questions. Key Changes Leading to the Shift in Data RolesWith every technological advancement their comes new players to the field. The difference is here is that the job description already existed. We were only missing a title. But from the traditional Data team to the modern Data team, there are a few key changes that point directly to the rise of this niche field. Cloud warehouses (like Snowflake, Redshift, BigQuery) and the arrival of the DBT the foundational layer which can be built on top of modern data warehouses are the first two that come to mind. Then, the Software-as-a-Service (SaaS) tools like Stitch and Hevo are capable of integrating Data from a variety of sources, and the introduction of tools like Mode and Looker allows anyone interested in drawing insight from Data to do so on their own.Who Needs an Analytics Engineer? Small or Large Businesses?The short answer is it depends. But the general rule follows that while both large and small companies can benefit from having this professional on their staff, there are different things to consider. For example, a small business may be able to find what they need in a single individual. The Analytics Engineer is something of a jack-of-all-trades. Larger businesses, on the other hand, may already have a Data team in place. In this case, an Analytics Engineer adds to your team, something like an additional set of eyes increasing insight drawn from those large swathes of Data we spoke about earlier.So, what’s next for the role of Analytics Engineer? Who knows? The roles of any Data industry professional is constantly evolving. If you’re interested in Analytics Engineering, Machine Learning, Data Science, or Business Intelligence just to name a few, Harnham may have a role for you. Check out our latest Data & Analytics Engineering jobs or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 – 4999 or send an email to sanfraninfo@harnham.com. For our Arizona Team, contact us at (602) 562 7011 or send an email to phoenixinfo@harnham.com. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.