Who we are 

What do Airbnb, Kind and Salesforce have in common? They use Culture Amp every day to make their workplaces better and grow highly engaged employees. They also make up a community of over 2,000 organizations from around the globe who stand together to change the world of work.

With offices in Melbourne, San Francisco, New York, and London, Culture Amp isn’t just for fast-growing startups - we’re for every organization that wants to put culture first. By making it easy to collect, understand, and act on employee feedback, we enable People teams to make better decisions, demonstrate impact, and turn company culture into a competitive edge.

It’s what makes us the world’s leading employee feedback platform.

What is the opportunity?

We are searching for a Data Engineer to join our Camp in Melbourne to build, maintain and improve our analytical capabilities in product analytics and beyond. Your work will enable many parts of the business to make better decisions through the collection, analysis and democratisation of our data. This is a chance to have an amazing impact on one of Australia's top SaaS companies—and learn a lot in the process.

What will you bring to the Camp?

While we don’t expect familiarly with everything, we’re looking for someone with broad exposure to at least three of the below:

  • Experience building and maintaining data pipelines with modern tools such as Airflow, Luigi, Digdag or AWS Glue.
  • Familiarity with building the cloud infrastructure required for world-class analytics and business intelligence on AWS. That would include tools like Kinesis Firehose, EMR, S3, Redshift, and ElasticSearch.
  • Knowledge of columnar or distributed data processing systems, such as Redshift, Hive, Spark or Presto.
  • Best practice dimensional modelling techniques such as derived fact tables and type 2 slowly changing dimensions, and leveraging them in a business intelligence system such as Tableau.
  • Understanding of digital analytics systems such as Google Analytics, Adobe Analytics or similar.

Example activities

  • Partner with key stakeholders (product managers, product marketers, customer success coaches) to develop an event taxonomy that can power product analytics
  • Work with our infrastructure team to research, configure and test a unified logging layer using tools such as Logstash or Fluentd
  • Configure data engineering workflows using tools such as Airflow or DigDag
  • Write and deploy Ruby or Python scripts to export anonymised data from our platform
  • Design and implement a system to securely and reliably send our product usage data to third-party systems such as Google Analytics, Mixpanel or Amplitude
  • Apply dimensional modelling techniques, allowing our data to be interrogated by business users in a business intelligence tool such as Looker or Tableau

What does success look like?

In the end, we are only successful when we help others and drive real business outcomes. Our goal is to ensure we:

  • collect all the data we need or might need, and not too much more
  • are able to analyse the data to generate insights
  • democratise the data, so it's available to all with as little friction as possible
  • be advocates and models for data-informed decision making at Culture Amp

A few highlights from Culture Amp

If this sounds like you, we'd love to hear from you.





AWS, Python, Ruby, Elasticsearch, and Engineering


18 days ago - source