Senior Big Data Engineer - CPG eCommerce

Cincinnati, Ohio
US$120000 - US$130000 per annum + Additional Benefits

Senior Big Data Engineer - CPG eCommerce

$120,000 - $130,000 base annual salary with additional benefits

Cincinnati, OH

THE COMPANY

This multi-billion-dollar industry conglomerate is looking to bring in intelligent, passionate, top notch cloud-based big data engineers to join their innovative and expansive brand to help grow their R&D Analytics branch to inform various major business decisions.

If you are a forward-thinking self-starter looking to embark on a new career with one of the largest world-renowned businesses, this could be the next opportunity for you!

THE ROLE

As Senior Big Data Engineer, your skillset will be highly utilized by the data science team to help derive insights on various product and service offerings such as consumer behavior and mark downs etc. Specifically, you will be responsible for the following key tasks:

  • Gathering requirements and collaborating closely with the Data Scientists to translate into technical output
  • Knowing which questions will help to resolve which used case situations
  • Coding in Python and Spark to build data pipelines and back end ML support functions
  • Working in a cloud hybrid environment of Azure, GCP and migrating existing data into AWS

YOUR SKILLS AND EXPERIENCE

In order to be considered for the Senior Big Data Engineer position, you must have at minimum the following prerequisites:

  • A Bachelor's or higher degree in Computer Science/Engineering/related field
  • Seasoned commercial data engineering experience
  • A willingness to learn new technologies and tools and a passion for code
  • Strong previous professional collaboration experience with data science teams
  • Prior hands-on commercial experience with Python and Spark
  • Prior hands-on commercial experience with at least one of the following cloud services, preferably serverless: AWS, GCP, Azure

THE BENEFITS

  • $120,000 - $130,000 base annual salary depending on experience level
  • Additional annual bonus package paid out at the end of the year
  • Medical, Dental, Vision Insurance
  • Competitive PTO and STO packages
  • Relocation (as needed)
  • Higher education resources
  • An energetic, intelligent, and forward-thinking environment

***Unfortunately, the client is not able to offer sponsorship or transfer of sponsorship for those who need it either now or in the future.***

HOW TO APPLY

Please register your interest by sending your résumé to Kavya Kannan via the Apply link on this page.

KEYWORDS

Big Data, Data Engineering, Data Pipeline, Data Architecture, Design, Python, AWS, Real Time, Streaming, Batch Processing, ETL, ELT, Data Formatting, Data Structure, Data Modeling, Data Governance, Data Cleansing, ML, Deep learning, NLP, PyTorch, Petabytes, R&D, Data Science

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98504/KK39
Cincinnati, Ohio
US$120000 - US$130000 per annum + Additional Benefits
  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.

Weekly News Digest: 15th - 19th Feb 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.  KDnuggets: 10 resources for data science self-study If you are interested in getting into data science, there are two basic pathways that you can opt for. There’s the traditional college degree route or the self-study option, the latter of which is growing in popularity among aspiring data scientists. This informative article from KDnuggets provides some insightful tips for data science self-study, grouped into three main categories: Resources for building fundamental knowledge; resources for data science practice; and resources for networking and continuous studies. Resources for building fundamental knowledge:Massive Open Online Courses (MOOCs)Learning from a TextbookYouTubeKhan AcademyResources for Data Science practice:KaggleInternshipsResources for networking and continuous studies:MediumLinkedInKDnuggetsGitHub Find out more here. Analytics India Magazine: How machine learning streamlines risk management Abhaya K Srivastava, SVP at Northern Trust Corporation, recently spoke at the Machine Learning Developers Summit 2021. Srivastava delved into how different sectors including financial, healthcare and retail are making use of emerging technologies like AI and Machine Learning. One of the main takeaways from the speaker session was discussions around how Machine Learning can support how organisations streamline their Risk Management. Srivastava stated, “It is essential for us to establish the rigorous governance processes and policies that can quickly identify when the model begins to fail.” He continued, “The terms of AI are not new, but businesses and organisations have started using these technologies in a different way. We have noticed the influence of machine learning in business applications, ML is playing an important role in Risk Management and there has been a constant focus on how risks are being detected, reported, managed.” There are a range of different machine learning techniques that can be applied to support risk management. It is the role of organisations, and their partners to discover how these processes can be applied. Read more on this here. Information Week: 3 Ways to Empower Female Software Engineers on Your Team We think this is a great article from Information Week that acknowledges the importance of establishing greater diversity and inclusion within software engineering, in particular to empower women in the industry. The article focuses on three areas: Create an inclusive team:Building an inclusive team is a strategic process and should include making sure everyone has a voice and that the workplace is a safe place to take risks.Provide a support system:Support establishes trust and shows a commitment to the well-being of your people. When leaders support their employees, it can significantly affect job satisfaction and performance.Enable women to inspire othersThe first thing to do is make sure the women in your organisation have a seat at the table; they should have a say in the decision-making process. Even if you have a good understanding of these, it’s important to keep educating yourself and the wider team in order to implements processes and strategies that make for a truly inclusive team. Read more on this here.  TechRepublic: 8 must-read leadership books recommended by tech titans and innovators Are you looking for your next read to help you elevate your visibility and skill as a leader in the tech industry? Look no further, as TechRepublic have put together a list of leadership books recommended by notable leaders from within the industry. Here are a few: The Ride of a Lifetime (Robert Iger) - Recommended by Bill GatesDrop the Ball (Tiffany Dufu) - Recommended by Sheryl SandbergMindset (Dr Carol S. Dweck) - Recommended by Satya NadellsTrailblazer (Marc Benioff) - Recommended by Susan Wojcicki It’s valuable to have insight from leaders that are already leading the way for tech innovation in their field, inspiring and supporting future leaders to achieve great things too. Click here to read the full list of recommended leadership books from Bill Gates, Satya Nadella, Sheryl Sandberg, Tim Cook, and other notable industry leaders. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.

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. 

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