Analytics Data Engineer

Job description

Bolster is Australia's premier digital, creative and product agency for music and entertainment.

Our fast growing team work from a beautiful, naturally lit warehouse in Collingwood surrounded by great food and bars. Perks include great hookups from the industries we work in, twice a week yoga, frequent team retreats and a dog friendly office.

We’re looking for a data engineer help lead a major change in the way the music industry works with data.

You’ll own the top to bottom data strategy and architecture for:

  • Bolster’s internal data systems including cross-client behavioral tracking

  • Analytics projects to help grow and improve the entertainment industry. Check out Bigsound Buzz

  • Analytics features on Linktree. Linktree has gained massive popularity in the last year, with 1.8m users and gaining over 8500+ new signups a day. Some key users are Alicia Keys, Eminem, The Grammys, Starbucks, Crossfit, Jamie Oliver, Fender and Kahlua.


Our dream candidate will possess all of the following qualities :

  • Commercial data engineering experience, building data pipelines, design, big data warehouses and shipping features

  • Ability to lead your own department while working well with dependent teams

  • An interest in music, entertainment, culture and lifestyle industries

  • Personable, clear and constructive communication skills.

Technical Must Haves :

  • Experience with Redshift and one of: Presto/Athena, Hive, Hadoop, Google BigQuery and using them for best practice data architecture

  • Comfortable working with event stream data from an analytics platform like Snowplow, Adobe Analytics or GA360

  • Experience with ETL scheduling technologies with dependency checking, such as Airflow, as well as schema design and dimensional data modelling

  • Python and relevant libraries (e.g. Pandas and NumPy)

  • Advanced SQL in an analytics environment

Bonus Points :

  • Knowledge of NoSQL, particularly ElasticSearch highly desired

  • Experience with BI tools like Metabase, Looker, Tableau etc

  • Extensive knowledge of the big data tooling landscape and best practices