Data Driven Hiring For Data Professionals With Alooba - Episode 243

Summary

Hiring data professionals is challenging for a multitude of reasons, and as with every interview process there is a potential for bias to creep in. Tim Freestone founded Alooba to provide a more stable reference point for evaluating candidates to ensure that you can make more informed comparisons based on their actual knowledge. In this episode he explains how Alooba got started, how it is being used in the interview process for data oriented roles, and how it can also provide visibility into your organizations overall data literacy. The whole process of hiring is an important organizational skill to cultivate and this is an interesting exploration of the specific challenges involved in finding data professionals.

Monte Carlo LogoStruggling with broken pipelines? Stale dashboards? Missing data?

If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform!

Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, dbt models, Airflow jobs, and business intelligence tools, reducing time to detection and resolution from weeks to just minutes. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. Start trusting your data with Monte Carlo today!

Visit http://www.dataengineeringpodcast.com/montecarlo to learn more.

 


Hightouch LogoHightouch is the leading Reverse ETL platform. Your data warehouse is your source of truth for customer data. Hightouch syncs this data to the tools that your business teams rely on. Hightouch has a catalog of flexible destinations including Salesforce, HubSpot, Zendesk, NetSuite, and ad platforms like Facebook or Google. Hightouch is built for data engineers and is a natural extension to the modern data stack with out-of-the-box integrations with your favorite tools like dbt, Fivetran, Airflow, Slack, PagerDuty, and DataDog.

It’s simple — connect your data warehouse, paste a SQL query, and use our visual mapper to specify how data should appear in downstream tools. No scripts, just SQL. Get started for free at dataengineeringpodcast.com/hightouch


Your data platform needs to be scalable, fault tolerant, and performant, which means that you need the same from your cloud provider. Linode has been powering production systems for over 17 years, and now they’ve launched a fully managed Kubernetes platform. With the combined power of the Kubernetes engine for flexible and scalable deployments, and features like dedicated CPU instances, GPU instances, and object storage you’ve got everything you need to build a bulletproof data pipeline. If you go to dataengineeringpodcast.com/linode today you’ll even get a $100 credit to use on building your own cluster, or object storage, or reliable backups, or… And while you’re there don’t forget to thank them for being a long-time supporter of the Data Engineering Podcast!


Announcements

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
  • Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the world’s first end-to-end, fully automated Data Observability Platform! In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, ETL, and business intelligence, reducing time to detection and resolution from weeks or days to just minutes. Start trusting your data with Monte Carlo today! Visit dataengineeringpodcast.com/montecarlo to learn more. The first 10 people to request a personalized product tour will receive an exclusive Monte Carlo Swag box.
  • Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems. No more scripts, just SQL. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Get started for free at dataengineeringpodcast.com/hightouch.
  • Your host is Tobias Macey and today I’m interviewing Tim Freestone about Alooba, an assessment platform for evaluating data and analytics candidates to improve hiring outcomes for data roles.

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you describe what Alooba is and the story behind it?
  • What are the main goals that you are trying to achieve with Alooba?
  • What are the main challenges that employers and candidates face when navigating their respective roles in the hiring process?
    • What are some of the difficulties that are specific to data oriented roles?
  • What are some of the complexities involved in designing a user experience that is positive and productive for both candidates and companies?
  • What are some strategies that you have developed for establishing a fair and consistent baseline of skills to ensure consistent comparison across candidates?
  • One of the problems that comes from test-based skills assessment is the implicit bias toward candidates who test well. How do you work to mitigate that in the candidate evaluation process?
  • Can you describe how the Alooba platform itself is implemented?
    • How have the goals and design of the system changed or evolved since you first started it?
    • What are some of the ways that you use Alooba internally?
  • How do you stay up to date with the evolving skill requirements as roles change and new roles are created?
  • Beyond evaluation of candidates for hiring, what are some of the other features that you have added to Alooba to support organizations in their effort to gain value from their data?
  • What are the most interesting, innovative, or unexpected ways that you have seen Alooba used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on Alooba?
  • When is Alooba the wrong choice?
  • What do you have planned for the future of Alooba?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Liked it? Take a second to support the Data Engineering Podcast on Patreon!