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Data Engineer

London
£400 - £500 per day

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DATA ENGINEER
£400-£500 PER DAY
3 MONTH CONTRACT
FULLY REMOTE

As a Data Engineer you will have the chance to work for a health care consultancy in analysing local data sets using Python, SQL and Airflow.

THE COMPANY:

As a Data Engineer, you will be working for a health care consultancy who are a front-runner within the space. You will be working alongside other Data Engineers and Data Scientists in a fast paced environment.

THE ROLE:

As a Data Engineer, you will you will be heavily involved in ETL development using Python. Therefore as a Data Engineer you must be extremely skilled in Python and if you have exposure to Python libraries such a NumPy this is valuable. Alongside building robust Python code as a Data Engineer you will also be using SQL so experience with this programming language is also vital. You will analysing local data sets so a good understanding of Excel is also key. As a Data Engineer you should be familiar with tools such as Airflow for scheduling. As you will be working in a consultancy you must be comfortable working in a fast paced environment. Any experience within the health sector is highly advantageous.

YOUR SKILLS AND EXPERIENCE:

The successful Data Engineer will have the following skills and experience:

  • Extensive experience with Python
  • Good use of SQL
  • Good understanding of Excel
  • Commercial use of Airflow

THE BENEFITS:

  • A chance to work on important projects

HOW TO APPLY:

Please register your interest by sending your CV to Anna Greenhill via the Apply link on this page.

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921456/AG
London
£400 - £500 per day
  1. Contract
  2. Big Data

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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

The Dialogue: Keeping Data Secure While Working Flexibly

Last week, Peter Schroeter and Ryan Collins, head of DevSecOps at Upvest, and co-founder of RapidGroup, discussed how to keep Data secure while working flexibly.  Ryan brings to the table 12 years of experience from Server Administrator to CTO roles as well as experience as a Contractor. And as a business owner himself, he sees where the shortage falls and perhaps a way to fill the gap. Security is in the Spotlight Security is a priority for many businesses today. Avoiding negative PR has caused an internal shift in which companies take more care with their Data. There is also a Catch-22. In order to provide higher levels of security, businesses are slowing down their developers and software engineers, and taking more engineering time which in turn costs more money. Security before cost is becoming the new reality. The contradiction of deployment, project run time, and budgets are only part of the bigger picture. Compromise is key and follow these three tenets. 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You have to know how to get into the code, you have to know how to get in and do the CI workflows, etc. It’s almost Developer plus value-added skills or security engineer plus value-added skills. Remote Working Habits You Need Now Have a separated space set up for work.If you have a mix of people in office and those working remote, you have to make sure they’re communicating with each other.Rolling coffee breaks within Google Meet or something similar.Have a task management and time tracking system used by employees both on and offline.Build culture by picking at random two people and putting them together for a half hour to have a conversation that isn’t about work.  Startup vs Legacy Hiring Don’t box yourself in, but understand startups have a unique set of skills they need and most often without the budget to train someone. Whereas legacy businesses more often than not have the budget to train someone in the skillset they need. However, it’s important to note, the tech stack itself doesn’t really change. Best Practices for Async-Comm Teams Remember not everyone works in the same time zone. Don’t expect and immediate answer, and if you need an immediate answer, pick up the phone. Make sure your team has remote tools such as Slack or Google Meet and is doing most of their communication this way, even if they are in an office. If you don’t, your remote workers could be missing key information. The Future of DevOps and Data Security Many businesses may see a shift toward a more open working environment which is a good balance for what works best for talent and is good for productivity as well. Ultimately, we’re all solving the same challenges What is most important when it comes to keeping Data secure? Most important is getting people, systems, and education in place to do something in the first place. In other words, build from concept rather than moving too fast and breaking too many things. How Can Prospective Candidates Prepare? Focus on continuous learning and getting your skillsets like automation tools. If you really want to get involved with security side and SRE, you really have to get involved with the development side, too. Using the modern tech stacks like the GOLANG, the RUST, the SWIFT on the mobile side, and there’s always new pieces to the puzzle.There’s room for all types of relationships. Whether you’re looking for a long-term role, a short-term role, or something in between, DevOps is a never-ending project, so continuous learning is key for both candidate and company. You can watch the full conversation below:

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03. December 2020

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