Senior Analytics Consultant – Transport Modelling
Durham, County Durham / £43000 - £55000
£43000 - £55000
Durham, County Durham
Senior Analytics Consultant
Remote (office work optional)
Up to £55, 000
A leading Engineering Consultancy is looking for a Senior Analytics Consultant to join their team to enhance their software and analytics products.
This company is an Engineering Consultancy and Asset Management company with a focus on infrastructure, roads, and railways. They are partnered with national and local Government bodies, as well as national transport networks.
The teams are very cross-functional and usually consist of DevOps, Testers, Product Owners, Data Engineers, Data Architects, and Stakeholders. This role will see you taking raw data and building models to deploy software products on top of the analytics this team already builds, as well as aiding in decision-making and stakeholder management.
The role and responsibilities
- Stakeholder management
- Solutions design and PoC work
- Choosing relational databases for scaling
- Code reviews and setting standards
- Building Transport Models
Your skills and experience
- Experience with Transport Modelling (essential)
- Experience with Python and SQL
- Experience as a Data Analyst
- Up to £55, 000 salary with up to 16% pension contribution
- Totally remote work with the option to go into a local office
- Working hours between 10:00-16:00, with flexibility on hours and days
- Learning and upskilling initiatives
Keepers of the Data Kingdom: the Analytics Engineer | Harnham US Recruitment post
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 email@example.com. For our Arizona Team, contact us at (602) 562 7011 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
How Advanced Analytics and Customer Engagement Create Insight for Your Business | Harnham US Recruitment post
Have you ever wondered why your favorite store stopped carrying an item you liked to purchase? Or how you discovered a new item to fit the bill for what you were searching for? Consider counterintuitive holidays where the stores are packed, but the checkout lanes are light with few cashiers. On the flip side, there may be opportunities in stores that have ensured they have plenty of product in stock, have extra staff to help, and through it all have managed to make the experience seamless.This last imagining is what happens when you bring Advanced Analytics into your business to gather insights and create customer engagement for people who will return again and again to your store and to buy your product. This isn’t just for brick-and-mortar stores, this includes digital and e-commerce businesses as well. But the big question here is, how did they know to hire extra staff, make sure there was enough product on hand, and not only retained former customers, but made new customers? The motto ‘know your customers’ holds true, even in, and especially in, today’s world of social media marketing, e-commerce shops, review opportunities, and more. Enter Advanced Analytics. The next step up from the Analytics of Business Intelligence to offer you and your business a birds-eye view of what your customers want, how they want it, and how you can ensure their experience keeps them returning, and opening doors to new customers as well. TRADITIONAL BUSINESS INTELLIGENCE (BI) VS ADVANCED ANALYTICS Business Intelligence gives historical performance Data. What have customers bought or thought in the past. This information has been used to inform how to improve processes now, for the next sale, call, or booking. Advanced Analytics, however, offers not only a system in which to capture historical Data, but can work with more complicated systems, and handle the massive amounts of Data businesses capture every day. Think of Advanced Analytics as the change agent who comes in to solve the more complicated issues. While it may still gather the same information, it will use the information to determine why something is working, and if something isn’t working, what is the root cause of the problem. If customers are returning again and again, what is bringing them back, and how can they repeat it and improve it for the future. Below are three types of analytics each with its own specialty to help you make more informed decisions to move your business forward. 4 BUSINESS OPERATIONS ADVANCED ANALYTICS SHINESGaining clear insights about your business involves more than just the experiences of your customers. The driving force behind happy customers are the operations of your business. From the supply chain to marketing to Human Resources, every department plays a role in the Customer Experience. So, what better way to use Advanced Analytics than to ensure the root of your business is running well which will be key to ensuring that smooth customer experience. · SUPPLY CHAIN ANALYTICS – Market demand is at an all-time high and supply is…well, it’s stuck a bit. But regardless of what’s being moved, where, and how, the remote workforce, globalization, and necessary manufacturing plants to handle the loads are making things more complicated than ever before. Advanced Analytics can help businesses plan for what will be in demand not only using past performance indicators, but also predictive modelling scenarios to try to meet the pain points of supply and logistics.· OPERATIONAL ANALYTICS – Changing market demands, adaptable processes, and flexibility in how operations are executed are all signs Advanced Analytics ha a place at the very heart of your organization. In this scenario, bits of seemingly unconnected Data come together to help imagine process alignment with market demand, and craft better insights for business.· RISK ANALYSIS – Cloud-based tools available to help identify management of massive amounts of Data with predictive insights using Advanced Analytics.· HUMAN RESOURCE ANALYTICS – To find and retain top talent, it’s important to ensure your business knows what they need, why they need it, and who can meet their requirements. Advanced Analytics can offer HR the chance to predict and evaluate how a prospective employee may do in your organization. Ready to take the next step in getting a birds-eye view of your business? Consider Advanced Analytics. Imagine knowing not only the historical Data which has kept your business moving forward, but using the near real-time Data streams from omnichannel sources to help you plan for the future of your business with future-predictive insights. If you’re interested in Digital Analytics roles, a career in Advanced Analytics, Machine Learning or Robotics just to name a few, Harnham may have a role for you. 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 firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
What’s Hot in NYC’s Data Market? Modern Analytics Engineering is on the Rise
New York has always set the stage for what’s next. When it comes to the latest in the tech stack, it’s modern Analytics Engineering is the latest addition to the Data and Analytics industry. The role of Analytics Engineer is one of the newer positions in the world of Data, and in NYC, a hub of media, advertising, and e-commerce – it’s emerging as one of the most in-demand markets in New York and beyond.
Why You Might Need an Analytics Engineer
Data-driven businesses interested in building value for their customers often turn to a mix of Analytics and Data Modelling Engineer. The Data Engineer creates the infrastructure, platform development, and Data movement for the purpose of Machine Learning and Analytics downstream. Ultimately, the Analytics Engineer role is quite similar to the typical Data Engineer but differs in that it doesn’t involve platform development or infrastructure the same way.
Analytics Engineering is a relatively new term within the last five years and are coming into this field from a variety of backgrounds. But the most in-demand background moving into this role is Data Engineering. Why? For the most part, it’s those individuals who can not only script in Python but also do Python programming on the backend.
Key Aspects of this Role:
- Warehouse architecture (e.g., Snowflake, Redshift, BigQuery), and Data Modeling with a popular and relatively new tool dbt (originally Fishtown Analytics), for use by Analysts.
- ETL Development
- Data visualization
- Other tech such as Fivetran, Stitch, and Python
With SQL and Data modelling being the real meat and potatoes of the position, people often move into an Analytics Engineering position that requires little Python experience – however, the salary you can expect if Engineering or Data Science experience and proficiency in Python is substantially higher. It poses an interesting opportunity for Analysts, Data modellers, and Data visualization folks interested in learning a modern engineering stack to make a transition into a more technical, and higher-paying role.
Why You May Want to Consider an Analytics Engineering Role
People move into this role from careers as Analysts, Data Scientists, Data Engineers, and even Software Engineers, a unique career progression in this industry. For the already heavily technical professionals – this is a role that provides both engineering challenges and the chance to work close to the business. Wherever you are on your career journey, Analytics Engineer is a great opportunity from a career growth perspective and can help get you where you want to go. You’re no cog in the wheel here. As an Analytics Engineer, you can help drive decisions that make an impact for your company.
Analytics Engineers on Your Team Can Drive Value for Your Business
Though this position is relatively new in the grand scheme of technological advances to help drive business, it is in demand and growing exponentially. So, it’s important to know if you’re business needs someone to fill this role, you need to know what you’re looking for. For companies, whose main objective is making Data-driven decisions regarding customer retention, marketing campaign conversion, supply chain analytics, etc.
The role of the Analytics Engineer can be a perfect addition to both managing large amounts of Data coming into the businesses and helping drive value.
Take a look at our latest Analytics Engineer jobs here or get in touch with one of our expert consultants to find out more:
For our West Coast Team, contact us at (415) 614 – 4999 or send an email to firstname.lastname@example.org.
For our Arizona Team, contact us at (602) 562 7011 or send an email to email@example.com.
For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to firstname.lastname@example.org.
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