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SENIOR DATA ENGINEER

Amsterdam, North Holland
€55000 - €65000 per annum
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SENIOR DATA ENGINEER

€55.000 - €65.000

AMSTERDAM

Ben jij een Senior Data Engineer op zoek naar een nieuwe uitdaging? Dan is dit jouw kans! Dit data gedreven E-commerce bedrijf in Amsterdam is op zoek versterking van het Data Engineering team. Jouw focus wordt om proof of concepts te bouwen en de bestaande dataplatforms aan te passen om data efficiëntie en stabiliteit te garanderen. Dit is een snelgroeiend, internationaal bedrijf binnen de steeds veranderende E-commerce-industrie.

Het bedrijf

Je gaat werken voor een wereldleider op het gebied van E-commerce, die wil voortbouwen op zijn data gedreven cultuur. Jij helpt mee aan de vernieuwing en verbetering van de bestaande dataplatforms en de data te transformeren. Het bedrijf beschikt over internationale teams en moedigt samenwerking en innovatie aan. Het doel is om marktleider te worden en het bieden van de best mogelijke service aan klanten.

De rol

Als Senior Data Engineer ben je verantwoordelijk voor het helpen creëren van nieuwe en schaalbare pipelines en applicaties en het verzamelen en transformeren van grote hoeveelheden ongestructureerde data.

Je doet dit door:

* Het uitvoeren van grootschalige datamining van ongestructureerde gegevens, die afkomstig zijn uit verschillende bronnen. Deze worden vervolgens getransformeerd.

* Samenwerken met mensen uit verschillende teams, allemaal in een agile omgeving.

* Toepassen van best practices op het gebied van engineering op de ingezette modellen.

Jouw ervaring en vaardigheden

- Een ervaren programmeur, en ruime ervaring met het gebruik van Python of Scala en shell-scripting zoals SQL.

- Een sterke achtergrond in datawarehousing en ervaring met tools zoals Redshift, Cassandra en Hive.

- Goede kennis en ervaring met MySQL, Oracle en PostgreSQL.

- Ruime ervaring met het werken met AWS.

- Bekend met het creëren van ETL-pipelines voor datawarehousing.

Arbeidsvoorwaarden

Naast jouw competitieve salaris wordt ook het onderstaande geboden:

- Je komt te werken in het gezelligste internationale team van Data Engineers in Amsterdam!

- Je krijgt de kans om met de nieuwste technologieën te werken en jouw technische kennis te ontwikkelen.

- Je maakt deel uit van een snelgroeiend en veranderend bedrijf met mooie kansen en doorgroeimogelijkheden.

Heb jij interesse?

Word jij enthousiast van bovenstaande beschrijving? Reageer dan met jouw CV via de sollicitatielink. Heb jij vragen? Stuur dan een e-mail naar: Mathieu Wilken.

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55112/MW
Amsterdam, North Holland
€55000 - €65000 per annum
  1. Permanent
  2. Business Intelligence

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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.

It Takes Two: Data Architect Meets Data Engineer

Information. Data. The lifeblood of business. Information and data are used interchangeably, gathered, collected, and analysed to create actionable insights for informed business decisions. So, what does that mean exactly? And to that end, how do we know what information or data we need to make those decisions? Enter the Data Architect. The Role of a Data Architect Just like you might hire an architect to sketch out your dreamhouse, the Data Architect is a Data Visionary. They see the full picture and can craft the design and framework creating the blueprint for the Data Engineer, who will ultimately build the digital framework. Data Architects are the puzzle solvers who can take a jumble of puzzle pieces, in this case massive amounts of data, and put everything in order. It’s their job to figure out what’s important and what isn’t based on an organisation's business objectives. Skills for a Data Architect might include: Computer Science degree, or some variation thereof.Plenty of experience working with systems and application development.Extensive knowledge and able to deep dive into Information ManagementIf you’re just starting your Data Architect path, be prepared for years of building your experience in data design, data storage, and Data Management. The Role of a Data Engineer The Data Engineer builds the vision and brings it to life. But they don’t work in a vacuum and are integral to the Data Team working nearly in tandem with the Data Architect. These engineers are building the infrastructure – the pipelines and data lakes. Once exclusive to the software-engineering field, the data engineer’s role has evolved exponentially as data-focused software became an industry standard. Important skills for a Data Engineer might include. Strong developer skills.Understand a host of technologies such as Python, R, Hadoop, and moreCraft projects to show what you can do, not just talk about what you can do – your education isn’t much of a factor when it comes to data engineering. On the job training does it best.Social and communication skills are critical as you map initial designs, and a love of learning keeps everything humming along, even as technology libraries shift, and you have to learn something new. The Major Differences between the Data Architect and Data Engineer RolesAs intertwined as these two roles might seem, there are some crucial differences. Data Architect Crafts concept and visualises frameworkLeads the Data Science teams Data Engineer Builds and maintains the frameworkProvides supporting framework With a focus on Database Management technologies, it can seem as though Data Architect and Data Engineer are interchangeable. And at one time, Data Architects did also take on the Data Engineering role. But the knowledge each has is used differently.  Whether you’re looking to enter the field of Data Engineering, want to move up or over with your years of experience to Data Architect, or are just starting out. Harnham may have a role for you. Check out our current opportunities or get in touch with one of our expert consultants to learn more.  

Eoin Pierce

Eoin Pierce

26. November 2020

News

The Search For Toilet Paper: A Q&A With The Data Society

We recently spoke Nisha Iyer, Head of Data Science, and Nupur Neti, a Data Scientist from Data Society.  Founded in 2014, Data Society consult and offer tailored Data Science training for businesses and organisations across the US. With an adaptable back-end model, they create training programs that are not only tailored when it comes to content, but also incorporate a company’s own Data to create real-life situations to work with.  However, recently they’ve been looking into another area: toilet paper.  Following mass, ill-informed, stock-piling as countries began to go into lockdown, toilet paper became one of a number of items that were suddenly unavailable. And, with a global pandemic declared, Data Society were one of a number of Data Science organisations who were looking to help anyway they could.  “When this Pandemic hit, we began thinking how could we help?” says Iyer. “There’s a lot of ways Data Scientists could get involved with this but our first thought was about how people were freaking out about toilet paper. That was the base of how we started, as kind of a joke. But then we realised we already had an app in place that could help.” The app in question began life as a project for the World Central Kitchen (WCK), a non-profit who help support communities after natural disasters occur.  With the need to go out and get nutritionally viable supplies upon arriving at a new location, WCK teams needed to know which local grocery stores had the most stock available.  “We were working with World Central Kitchen as a side project. What we built was an app that supposed to help locate resources during disasters. So we already had the base done.” The app in question allows the user to select their location and the products they are after. It then provides information on where you can get each item, and what their nutritional values are, with the aim of improving turnaround time for volunteers.  One of the original Data Scientists, Nupur Neti, explained how they built the platform: “We used a combination of R and Python to build the back-end processing and R Shiny to build the web application. We also included Google APIs that took your location and could find the closest store to you. Then, once you have the product and the sizes, we had an internal ranking algorithm which could rank the products selected based on optimisation, originally were based on nutritional value.”  The team figured that the same technology could help in the current situation, ranking based on stock levels rather than nutritional value. With an updated app, Iyer notes “People won’t have to go miles and stand in lines where they are not socially distancing. They’ll know to visit a local grocery store that does have what they need in stock, that they’ve probably not even thought of before.” However, creating an updated version presented its own challenges. Whereas the WCK app utilised static Data, this version has to rely on real-time Data. Unfortunately this isn’t as easy to come by, as Iyer knows too well:  “When we were building this for the nutrition app we reached out to groceries stores and got some responses for static Data. Now, we know there is real-time Data on stock levels because they’re scanning products in and out. Where is that inventory though? We don’t know.” After putting an article out asking for help finding live Data, crowdsourcing app OurStreets got in touch. They, like Data Society, were looking to help people find groceries in short supply. But, with a robust front and back-end in place, the app already live, and submissions flying in across the States, they were looking for a Data Science team who could make something of their findings.  “We have the opportunity,” says Iyer “to take the conceptual ideas behind our app and work with OurStreets robust framework to create a tool that could be used nationwide.” Before visiting a store, app users select what they are looking for. This allows them to check off what the store has against their expectations, as well as uploading a picture of what is available. They can also report on whether the store is effectively practising social distancing. Neti explains, that this Data holds lots of possibilities for their Data Science team: “Once we take their Data, our system will clean any submitted text using NLP and utilise image recognition on submitted pictures using Deep Learning. This quality Data, paired with the Social Distancing information, will allow us to gain better insights into how and what people are shopping for. We’ll then be able to look at trends, see what people are shopping for and where. Ultimately, it will also allow us to make recommendations as to where people should then go if they are looking for a product.”  In addition to crowdsourced information, Data Society are still keen to get their hands on any real-time Data that supermarkets have to offer. If you know where they could get their hands on it, you can get in touch with their team.  Outside of their current projects, Iyer remains optimistic for the world when it emerges from the current situation: “Things will return to normal. As dark a time as this is, I think it’s going to exemplify why people need to use Artificial Intelligence and Data Science more. If this type of app is publicised during the Coronavirus, maybe more people will understand the power of what Data and Data Science can do and more companies that are slow adaptors will see this and see how it could be helpful to their industry.”   If you want to make the world a better place using Data, we may have a role for you, including a number of remote opportunities. Or, if you’re looking to expand and build out your team with the best minds in Data, get in touch with one of expert consultants who will be able to advise on the best remote and long-term processes. 

Nick Mandella

Nick Mandella

14. April 2020

News

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