Data Engineer at Culture Amp

Data & People Science, Melbourne melbourne engineering
Description
Posted 11 days ago

Who We Are

What do Airbnb, Slack and Salesforce have in common? They use Culture Amp every day to make their workplaces better, along with over 2,500 other companies from around the globe, making up a community who stand together to improve 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 people & culture 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 a huge impact on transforming the world of work for the better—and learn a lot in the process.

What will you bring to the Camp?

While we don’t expect familiarity 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, dbt, or AWS Glue.
  • Interest in working with data streams using tools like Storm, Flink, Kafka, and Spark Streaming
  • Familiarity with building the cloud infrastructure required for world-class analytics and business intelligence on AWS. That would include tools like Kinesis, EMR, S3, Athena, 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, Mixpanel or similar.

Example activities

  • Work with our infrastructure team to research, configure and test a unified logging layer using tools such as Logstash or Fluentd
  • Implement, test, and deploy data pipelines using tools such as dbt or Spark
  • 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
  • Are advocates and models for data-informed decision making at Culture Amp 

A few highlights from Culture Amp: