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Senior Data Engineer - CPG eCommerce

Cincinnati, Ohio
US$120000 - US$130000 per annum + Additional Benefits
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Senior 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 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 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/KK46
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: 12th - 16th April 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.      Express Pharma: The five biggest data challenges for life sciences Life Sciences has grown exponentially over the past 12 months. As the COVID-19 pandemic devastated the world, Life Science companies were in a race against time to create a life-changing vaccine and help us all back on the road to recovery.  In 2019, the Life Science market was valued at around $7.5bn. After this year’s influx of activity, the market is estimated to grow by over double in the next decade, reaching $18bn by 2030.  However, despite the positive growth the industry has had, this doesn’t mean Life Sciences will be free of challenges. In fact, with such a spike in the amount of data held by so many Life Science companies as they tried to work on a vaccine, data storage is now one of the main concerns for anyone working within the field.  In this article by Express Pharma, Vimal Venkatram, Country Manager for Snowflake India, highlights the five key data hurdles Life Sciences will continue to have to overcome in the following decade. These include data performance, data exchange and collaboration, data quality, data management and scaling, and regulatory compliance.  Read the full story here.  Harnham: How can organisations tap into the huge pool of neurodiverse data talent? For many companies, the past year has led to an increased focus on diversity and inclusion within businesses – a fantastic step forward. However, when we think of diversity, we usually assume people are talking about gender, ethnicity, sexuality and perhaps even physical disability. One area that is regularly missed from discussion is that of neurodiversity.  An umbrella term coined by sociologist, Judy Singer, neurodiversity can cover a wide range of neurological conditions such as dyslexia, autism, ADHD, ADD and dyspraxia. Our head of internal recruitment, Charlie Waterman, explores why neurodiverse talent shouldn’t be overlooked, and how Data & Analytics specifically can do more to tap into and harness this incredible pool of talent.` Exploring how employers can create a smooth recruitment process, successful onboarding programmes and retention schemes, this article highlights how all of this can be tailored to be accessible for anyone with an invisible disability. To read more on this topic, click here. Computer Weekly: What has a year of homeworking meant for the DPO? Employers in a significant number of industries across the world have had to uproot from the office to working from home because of the COVID-19 pandemic. For many of these employers, it appears that remote working, or a hybrid model of working, will become the norm post-pandemic.  But what has this sudden shift meant for the likes of Data Protection Officers (DPOs)? Most of these professionals have had to get to grips with managing and handling sensitive data from the comfort of their own living room. According to data from IBM, 70 per cent of DPOs believe that the shift to remote working will increase the likelihood of data breaches. So how can DPOs enjoy the benefits and perks of working from home, without the stress of poorly managed or breached data? In this article by Computer Weekly, steps are outlined on how DPOs can work closely with IT teams to minimise any data risk that could happen. This includes: Not allowing DPOs access to everything if it’s not necessaryDiscouraging local storage of dataRegularly reviewing security standards To read the full article, visit the website here.  Solutions Review: The three best Data Engineering books on our reading lists There’s no better feeling than getting stuck into a really good book. Not only can it be a great way to escape the stresses of everyday life, but by continuously absorbing new information, your knowledge on a specific subject can grow immensely.  Any branch of Data & Analytics, but especially Data Engineering, requires employees to always be thinking one step ahead, staying on top of new trends and keeping up to date with specific coding languages. While everyone learns in very different ways, reading is a brilliant education tool. Whether you’re a visual learner, an auditory learner or a reading learner, books and audiobooks could be the key to expanding your knowledge.  Solutions Review provides Data Engineers with three of the best books on the market at the moment to help you keep on top of your professional development. Data Driven Science and Engineering by Brunton and KutzData Engineering with Python by Crickard An introduction to agile Data Engineering by using data vault 2.0 by Graziano To read more about each of these books, click here.  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.    

Talitha Boitel-Gill

Talitha Boitel-Gill

16. April 2021

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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