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DATA ENGINEER

Paris, Île-de-France
€50000 - €55000 per annum
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DATA ENGINEER
50K€ - 55K€
Paris

Au sein de cette start-up spécialisée en e-commerce où l'esprit d'équipe, la bonne entente et collaboration sont de mise. Vous serez passionné et enthousiaste à l'idée de partager et contribuer au développement de l'équipe data engineering.

Elle est actuellement à la recherche d'un profil Data Engineer, expert technique dans le milieu data qui sera en mesure de recueillir les données ainsi que de garantir leur pertinence, fiabilité et maximiser les données dans le but de former des vues de métiers actionnables:

LE POSTE:

En tant que Data Engineer, Vous serez en charge de fortifier et surveiller le système d'intégration des diverses sources de données. Votre expertise sur la gouvernance et qualité des données ainsi que l'architecture seront partagées à votre responsable Data.

Plus spécifiquement, vous serez amené à:

  • Améliorer la mise en place du Datalake, Datawarehouse
  • Établir un contrôle de la qualité des données
  • Mettre en place un data catalogue ainsi que de participer énergiquement au plan d'action de l'ensemble du domaine des données
  • Instaurer la récupération de data à travers diverses sources AFI, FTP
  • Installer les processus de transformation de celles-ci ainsi que les modèles data et régir les bases de données
  • Maximiser l'exploitation des données en établissant le partitionnement et calcul distribué.
  • Assurer la stabilité des environnements de production

LE PROFIL:

Diplômé(e) d'un Master spécialisé informatique décisionnelle ou Big Data, vous avez une bonne connaissance des écosystèmes data et avez un réel intérêt pour le machine learning:

  • Vous avez une excellente maîtrise des outils Python et SQL
  • Vous avez de l'expérience sur un outil ETL: Glue, Talend
  • Une maîtrise incontestable de AWS (Sagemaker, Redshift, S3…)
  • Une bonne compréhension des outils Big Data: Spark, Kafka, streaming
  • Une significative expérience de développement BI et plus précisément Tableau.
  • Une connaissance des méthodes de travail agiles SCRUM
  • Une première expérience avec les outils de développement Git, Docker, Bitbucket

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104352/AS
Paris, Île-de-France
€50000 - €55000 per annum
  1. Permanent
  2. Big Data

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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.

How Can Your Career In Big Data Help You To Accelerate Change?

Data & Analytics is fast becoming a core business function across a range of different industries. 2.5 quintillion bytes of data are produced by humans every day, and it has been predicted that 463 exabytes of data will be generated each day by humans as of 2025. That’s quite a lot of data for organisations to break down. Within Gartner’s top 10 Data & Analytics trends for 2021, there is a specific focus on using data to drive change. In fact, business leaders are beginning to understand the importance of using data and analytics to accelerate digital business initiatives. Instead of being a secondary focus — completed by a separate team — Data & Analytics is shifting to a core function. Yet, due to the complexities of data sets, business leaders could end up missing opportunities to benefit from the wealth of information they have at their fingertips. The opportunity to make such an impact across the discipline is increasingly appealing for Data Engineers and Architects. Here are a just a selection of the benefits that your role in accelerating organisational change could create. Noting the impact In a business world that has (particularly in recent times) experienced continued disruption, creating impact in your industry has never been more important. Leaders of organisations of a range of sizes are looking to data specialists to help them make that long-lasting impression. What is significant here is that organisations need to build-up and make use of their teams to better position them to gather, collate, present and share information – and it needs to be achieved seamlessly too. Business leaders, therefore, need to express the specific aim and objective they are using data for within the organisation and how it’s intended to relate to the broader overarching business plans. Building resilience Key learnings from the past year have taught senior leaders around the globe that being prepared for any potential future disruption is a critical part of an organisation’s strategic plans. Data Engineers play a core role here. Using data to build resilience, instead of just reducing resistance or limiting the challenges it presents, will ensure organisations are well-placed to move into a post-pandemic world that makes use of the abundance of data available to them. Big Data and pulling apart and understanding these large scale and complex data sets will offer a new angle with which to inform resilience-building processes.  Alignment matters An organisation’s ability to collect, organise, analyse and react to data will be the thing that sets them apart from their competitors, in what we expect to become an increasingly competitive market. Business leaders must ensure that their teams are part of the data-driven culture and mindset that an organisation adopts. As this data is used to inform how an organisation interacts with its consumers, operates its processes or reaches new markets, it is incredibly important to ensure that your Data Engineers (and citizen developers) are equipped and aligned with the organisation’s visions. Change is a continuous process, particularly for the business community. Yet, there are some changes that are unpredictable, disruptive and mean that many pre-prepared plans may face a quick exit from discussions. Data professionals have an opportunity to drive the need for change, brought about by the impacts of the pandemic, in a positive and forward-thinking way. In understanding impact, resilience and alignment, this can be truly achieved. Data is an incredibly important tool, so using this in the right way is absolutely critical. If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.

Georgina Garraway

Georgina Garraway

25. March 2021

News

Using Data Ethically To Guide Digital Transformation

Over the past few years, the uptick in the number of companies putting more budget behind digital transformation has been significant. However, since the start of 2020 and the outbreak of the coronavirus pandemic, this number has accelerated on an unprecedented scale. Companies have been forced to re-evaluate  their systems and services to make them more efficient, effective and financially viable in order to stay competitive in this time of crisis. These changes help to support internal operational agility and learn about customers' needs and wants to create a much more personalised customer experience.  However, despite the vast amount of good these systems can do for companies' offerings, a lot of them, such as AI and machine learning, are inherently data driven. Therefore, these systems run a high risk of breaching ethical conducts, such as privacy and security leaks or serious issues with bias, if not created, developed and managed properly.  So, what can businesses do to ensure their digital transformation efforts are implemented in the most ethical way possible? Implement ways to reduce bias From Twitter opting to show a white person in a photo instead of a black person, soap dispensers not recognising black hands and women being perpetually rejected for financial loans; digital transformation tools, such as AI, have proven over the years to be inherently biased.  Of course, a computer cannot be decisive about gender or race, this problem of inequality from computer algorithms stems from the humans behind the screen. Despite the advancements made with Diversity and Inclusion efforts across all industries, Data & Analytics is still a predominantly white and male industry. Only 22 per cent of AI specialists are women, and an even lower number represent the BAME communities. Within Google, the world’s largest technology organisation, only 2.5 per cent of its employees are black, and a similar story can be seen at Facebook and Microsoft, where only 4 per cent of employees are black.  So, where our systems are being run by a group of people who are not representative of our diverse society, it should come as no surprise that our machines and algorithms are not representative either.  For businesses looking to implement AI and machine learning into their digital transformation moving forward, it is important you do so in a way that is truly reflective of a fair society. This can be achieved by encouraging a more diverse hiring process when looking for developers of AI systems, implementing fairness tests and always keeping your end user in mind, considering how the workings of your system may affect them.  Transparency Capturing Data is crucial for businesses when they are looking to implement or update digital transformation tools. Not only can this data show them the best ways to service customers’ needs and wants, but it can also show them where there are potential holes and issues in their current business models.  However, due to many mismanagements in past cases, such as Cambridge Analytica, customers have become increasingly worried about sharing their data with businesses in fear of personal data, such as credit card details or home addresses, being leaked. In 2018, Europe devised a new law known as the General Data Protection Regulation, or GDPR, to help minimise the risk of data breaches. Nevertheless, this still hasn’t stopped all businesses from collecting or sharing data illegally, which in turn, has damaged the trustworthiness of even the most law-abiding businesses who need to collect relevant consumer data.  Transparency is key to successful data collection for digital transformation. Your priority should be to always think about the end user and the impact poorly managed data may have on them. Explain methods for data collection clearly, ensure you can provide a clear end-to-end map of how their data is being used and always follow the law in order to keep your consumers, current and potential, safe from harm.  Make sure there is a process for accountability  Digital tools are usually brought in to replace a human being with qualifications and a wealth of experience. If this human being were to make a mistake in their line of work, then they would be held accountable and appropriate action would be taken. This process would then restore trust between business and consumer and things would carry on as usual.  But what happens if a machine makes an error, who is accountable?  Unfortunately, it has been the case that businesses choose to implement digital transformation tools in order to avoid corporate responsibility. This attitude will only cause, potentially lethal, harm to a business's reputation.  If you choose to implement digital tools, ensure you have a valid process for accountability which creates trust between yourself and your consumers and is representative of and fair to every group in society you’re potentially addressing.  Businesses must be aware of the potential ethical risks that come with badly managed digital transformation and the effects this may have on their brands reputation. Before implementing any technology, ensure you can, and will, do so in a transparent, trustworthy, fair, representative and law-abiding way.  If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.

Henry Rodrigues

Henry Rodrigues

21. January 2021

News

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