Aunalytics Job Opening

Analytics Support Engineer


Location: South Bend, IN
Type: Full Time

Position Overview

Analytics Support works with all industry vertical and product teams as a resource for fixing and preventing data issues, solving engineering, analytics and visualization problems, creating internal support documentation, and contributing to external product and solution documentation.

We’re trying to build a cross functional team of diverse roles that cover as many skills as possible with a small team focused on one goal – reliably delivering up to date, correct, and on time data to our clients, from ingestion, through processing, to a final client facing solution.

  • Are you a data engineer with ingestion experience?
  • Do you have some knowledge of data science that you want to add to dashboards and alert systems to keep the data flowing smoothly?
  • Do you want to dig into someone else’s code to see what it does right, what it does wrong, and what it could just do faster and better?
  • Do you want to dig into data until you find the real reason that one number wasn’t quite right, and then explain to the client what you found, how we fixed it, and how we’ll prevent it from happening again

Then maybe we’re looking for you!

Essential Duties and Responsibilities

  • Identify and solve issues with data ingestion and processing, using various analytical tools, including Excel, Tableau, SQL, and proprietary data engineering tools
  • Solve problems with and optimize data processing and analytical dashboard calculations
  • Create and/or maintain documentation on current data products and issue solutions
  • Create and/or maintain testing and QA suites to help identify and solve data issues as quickly as possible
  • Work with internal and external teams to triage and solve issues, to learn current data and processes, and to help create standard, repeatable, optimized solutions
  • Become an expert in the data and solutions for one or more clients.

Preferred Skills

Hard Skills:

  • Data ingestion – we get data from a variety of sources that can fail at any time, for many reasons, sometimes silently. We need someone who understands these reasons, can identify them, and if we can’t prevent them from happening, at least stop it from happening silently.
  • Data engineering – SQL, Pig, Python, whatever. We have our own tools, so the concepts here are more important than the specifics, but you need to be able to read and understand someone else’s code or data flow enough to find errors, and to explain what it does.
  • Data analysis – Tableau, Excel, Python. We sometimes need to sift through millions of rows and dozens of inputs to see which one is causing the problem – or look at a dashboard and see one number that gives us the right clue.
  • Visualization – Tableau again, some mobile app work in JSON. We might be analyzing why something isn’t working in a current solution, or helping an analyst figure out a better, or at least different, way to present data – so knowing the tools and some visualization best practices
    could be very valuable.
  • Documentation – document the data, document the issues, document the process, so we can get better, faster, stronger. We should only have to solve a problem once – if we can’t stop it from happening again (and that’s obviously the main goal), then we should have a document process for how to deal with it when we see it again.
  • Optimization – sometimes everything works, but it doesn’t work efficiently – And no one wants to wait 10 minutes for a dashboard to load, or 4 hours for a data flow to run. Knowing some optimization techniques can add a lot of value to an already working product.
  • Data science – We hope to use this to help us build intelligent dashboards or alerts that tells us when something’s gone wrong before we finish processing – or at least before the client tells us their data is bad?

Soft Skills:

  • Data curiosity – you need to want to dig down and really look at the data to find the real problem – to never assume the first thing you found is what’s wrong. Sure, sometimes it is – but sometimes it’s just a symptom if a bigger, or smaller, issue.
  • Attention to detail – often the biggest problems start with the smallest issues, and we need to notice these tiny details. If you can see one number in a thousand that looks off, or one field of 20 mapped to the wrong calculation, or even a title bar out of alignment on a dashboard, then
    you might be able to help us find some needles in some haystacks.
  • Quick learner – you can’t know all the data, so you need to be able to drop into a problem and understand the data and the deliverable quickly, sometimes with limited documentation.
  • Knowledge retention – but once you’ve learned a client’s data, you won’t have time to relearn it every time there’s an issue – you’ll have to become, and stay, an expert in at least some clients’ data, so we don’t spend time starting from scratch for every problem.
  • Communication – you have to be able to explain the details of what you’ve found to the technical teams so they can make fixes- but you also need to be able to explain the solution at a high level to a very non-technical client success team, or even the client, and that is often the harder task. Sometimes you’ll get to talk to them, but sometimes you’ll have to write an email or a document, so you need to be able to make yourself understood to both audiences, and in both mediums.
  • Team player and lone wolf – you’ll really need to be able to do both. Often you’ll be on your own trying to solve a problem, but you also need to know when to ask for help, both from your teammates, and from the development and product teams – we may have skills, but they know what they built, and what it’s supposed to do. You’ll also need to pitch in when your particular skills or knowledge are needed, or just when another set of eyes, or someone to bounce ideas off of, are needed on a problem
  • Client focused – at the end of the day, our only goal is to give the client a seamless data and analytics experience. Working toward that goal should be our priority in everything we do, and should inform our sense of urgency, our rigorous research, solutions, and documentation, and our drive to solve problems before they happen.

What's In It For You?

  • Opportunity to work with a rapidly expanding tech company in the booming field of data science and cloud computing, alongside some of the brightest minds in the industry.
  • Opportunity to work with cutting-edge technology in a casual, fun environment
  • Opportunity to be a part of a local company committed to making a difference in our community
  • Chance to work with a rapidly expanding tech company
  • Flexible schedule and paid time off
  • Free snacks and an unlimited supply of coffee
  • Social events such as happy hours, game nights, holiday parties, birthday celebrations, movie days, ice cream sundae bars, fancy coffee carts, company softball team, etc.
  • Competitive salary and benefits package including health, vision, dental, and life insurance

To apply for this job, email your resume and cover letter to careers@aunalytics.com.