Harnham
SEARCH
Shortlist

Data and Technology jobs

Whatever technology or field of focus is your passion, we share your commitment and can help you progress within it.





harnham on
data engineering

What We Do

We source the people who enable and optimise the technologies that make data possible.

From the Data Engineers who design and build data platforms, and those that manage data quality and data governance, through to Business Intelligence and Data Visualisation professionals, our Data and Technology team recruits for roles that sit behind effective analytics.

Our dedicated teams across the Data and Technology verticals have a genuine understanding of the skills, technologies, tools and environments required for the job as well as the people who make it happen. We are truly specialised in data and analytics recruitment throughout this sector and analyse the market thoroughly.

What sets us apart?

Our specialist focus encompasses roles in core verticals: Big Data and Data Engineering, Data Architecture, Business Intelligence and Data Warehousing, and Data Management and Data Governance.

We have the knowledge, the network and the required drive to find the best candidates on the market, as well as working with some of the most exciting data businesses around.

If you’re hoping to change careers or are looking for the right talent to fill an opening, Harnham can help.

Meet the team

Latest Jobs

Data Engineer
Salary

£65000 - £85000 per annum

Location

London

Description

A chance to work for one of the leaders in telecommunications where you can develop and enhance your skills.

ADD TO SHORTLIST
Business Intelligence Analyst
Salary

£35000 - £40000 per annum + benefits

Location

City of London, London

Description

If you have experience working with SQL, ETL tools as well as Cloud-based Data warehouse's and data visualisation tools then click below...

ADD TO SHORTLIST
Senior BI Analyst Developer
Salary

£60000 - £70000 per annum + benefits

Location

London

Description

Great opportunity for an experienced BI Developer to join a really dynamic BI team who are going to be a central consultancy servicing all business areas

ADD TO SHORTLIST
Data Engineer
Salary

£55000 - £70000 per annum

Location

London

Description

New role just in - Data Engineer for a growing e-commerce business based in Central London.

ADD TO SHORTLIST
Python Developer
Salary

£50000 - £70000 per annum + Bonus

Location

London

Description

work on the beginning of a brand new digital transformation journey

ADD TO SHORTLIST
Cloud Engineer
Salary

£60000 - £65000 per annum

Location

London

Description

Join a leading fin-tech as a Cloud Engineer where you will be responsible for designing, building and managing automated software deployment solutions.

ADD TO SHORTLIST

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

What Does The Fourth Industrial Revolution Look Like?

We’re in the next stage of the fourth Industrial Revolution and technologies continue to merge. No longer is advancement as simple as adding “tech” to the end of a word - sorry Fintech, InsurTech, HRTech, and the rest. Now technologies stand together as each becomes a separate piece of how tech operates in the business world. AI and IoT have merged to become AIoT. Data is as much commodity as it is information to fuel business growth. Computer Vision partnered with AI is teaching computers to convert their ones and zeros to images humans take for granted.   In a word, it’s a transformative time for every industry and every industry is taking advantage of the benefits in one way or another. Smart manufacturing. Human Resources. Marketing. Even insurance has joined the party. But, with so many advancements, we thought we’d take a look at just the tip of the iceberg, starting with A, B, and C.  AI Meets IoT  We’ve all heard how AI and the Internet of Things (wearable and smart devices etc.) are being used in the Health sector. With the kind of real-time Data available, patients, insurers, and medical professionals can map out health plans based on wearable devices to track patient health and encourage preventative care.  Indeed, one insurance company is embracing these Data trends to ramp up the speed and efficiency of their data. Using Machine Learning and IoT sensors to develop an AI-based solution, customer information is used to match clients with the right policies tailored to their needs.  Car insurance is another industry to benefit. Insurers are able to collect real-time driving data which they can analyse to determine risk or offer discounted policies for good driving. This kind of information can also be used to revisit and reconstruct accident scenes to figure out what happened and who’s at fault.  Big Data, Big Money We’ve all heard the phrase ‘Data Is The New Oil’ by now, which I’m sure we can all agree, just means Data is a resource everybody wants and is willing to pay a lot for. But the differences between Data and Oil are two-fold; Data has the potential to be infinite, and it tells us about what oil cannot; the human experience.  Cloud technologies, edge hardware, and the IoT have helped shape the digitisation of objects, people, and organisations. From sensors to wearable devices, more and more data is being collected, allowing us to be more connected than ever before. It’s also providing more information to the tech giants than ever before. For example, Amazon’s Ring doorbell is logging every motion around it and can pinpoint the time to millisecond.   Add these technologies to Natural Language Processing (NLP) and watch the world around us draw value from and understand our Data like never before. The wave of Big Data value shows no signs of slowing down. Computer Vision in Business In the last few years, Computer Vision has been making great strides in the business world. Yet the Data required for processing power and memory can still be impacted by image quality. The opportunities  are alive with possibility and, from small businesses to enterprise solutions, Computer Vision has seen a variety of industries finding practical business uses.  Below are just a few additional areas Computer Vision is making its mark. Facial Recognition – providing surveillance and security systems in such areas as police work, payment portals, and retail stores.Digital Marketing – sorting and analysing online images to target ad campaigns to the right audiences.Financial Institutions –preventing fraud, allowing mobile deposits, analysing handwriting, and beyond. With the global market for fourth industry technologies predicted to be between $17.4 billion and $48.32 billion by 2023, now is the time to find your focus within the industry.  Ready to take the next step in your career? Whether you’re interested in AI, Big Data and Analytics, Computer Vision or more, we may have a role for you. Take a look at our current opportunities or get in touch with one of our expert consultants to find out more.  

Krishen Patel

Krishen Patel

05. March 2020

What defines a Data Architect?

Data Analyst. Data Wrangler. Data Architect? If you like pulling together threads of a company’s Data into one cohesive point, you may want to consider a Data Architect role. But what exactly is a Data Architect and how does it differ from a Data Engineer? Data Architect vs. Data Engineer As businesses continue to combine their Data and business strategies into one, they are beginning to understand to the need for a variety of Data Analysts. But as important as it is to have someone build your platform and begin pipeline processes, there is also need for someone with vision. Someone who can see patterns and designs. Someone who has end-to-end vision and can see how the patterns flow through your processes. This is your Data Architect. Data Engineers, on the other hand, lay the foundation for your Data platform. They draft the blueprint. After all, you can’t build a house without a blueprint first, right? The Data Engineer is at the beginning of the process, so the rest of the team can do their parts. But it’s the Data Architect who pulls it all together. THE ROLE OF THE DATA ARCHITECT  If you’re considering your next career move and wondering if Data Architecture is for you, here are some typical requirements. A typical Data Architect will: Meet with stakeholders to understand business needs and translate them into technical requirements using ETL techniques to develop Data ArchitectureUnderstand their full Data lifecycle to provide technical architecture leadershipDesign a real-time data pipeline ecosystem and how to make it scalable usingDevelop Big Data Architecture in an AWS environmentBe educated to a degree level in a numerate discipline (Mathematics, Statistics, Computer Science, Computer Engineering)• Have proven experience in a commercial environmentHave advanced Cloud Computing Ecosystem experience with AWS (GCP or Azure also considered)Have proven Big Data Ecosystem experienceHave proven Big Data Architecture experience in a commercial environment Have proven Data Engineering experience in a commercial environment Though the likes of Google, IBM, and others have ramped up their education efforts, and online courses traditional universities offer a variety of Data Science degrees, there is still a shortage of professionals in the industry. So can businesses simplify and automate processes without the right people in place? Businesses Step Up Their Data Strategies Though there are easier ways to get the information a business needs through rented predictive modelling or an already drafted Data Science model, it doesn’t give the true value of Data. Add in new regulations, requirements, and new Data which offer new insights, and the impact on business is profound.   It’s time for business to start ensuring that their Data teams are treated as critically as possible. Time to lay a path of progression, a pipeline, of systems and processes for the creation and production of Data. After all, simply optimising your Data will only get you so far. Enterprise-wide Data systems are more than wrangling and analysing Data.  Most importantly, businesses need to ensure they have the right people in place. They also need to understand what they need and why they need it. This is a key part of Data Strategy and with the right people in place, can put your business ahead of the competition.  Digging Deeper into Requirements for Top Talent While the standard requirements for a Data professional are to be educated to a degree level in things like Computer Science and Mathematics, technical skills, and experience within certain industries, for the natural progression from Data Analyst to Data Architect, there’s a bit more nuance to consider. Whether your business is just getting started in Data Science or you’re ready to start growing an existing team, there are some things you may want to focus on when looking for your Data Architect role. Define and determine how to keep projects streamlined with repeatable processes. Pivot between guiding team members through the pipeline and explaining insights to executives and stakeholders. Determine the right format for the right project. Determine when and when not to use automation to integrate Data. Visualise and extract models to predict future events and describe the process. In other words, be able to interpret Data to ensure reliability of the best approach. With the right talent in place, your teams can collaborate and build on their shared expertise to ensure Data is analysed and understood to the best benefit of your business. If you like solving puzzles, pulling disparate threads together into organised systems, and have experience as analysing and collecting Data, we may have a role for you.  Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.  

Joshua Carter

Joshua Carter

20. February 2020

Recently Viewed jobs