Data Engineer
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Posted almost 5 years ago
IN A NUTSHELL
Help us make better decisions by getting our (many) data pipelines flowing smoothly and sensibly into a well-architected warehouse. Bellroy loves to balance art with science; using data to inform and test our theories, and iterating towards Truth.
We need your help to build, improve and maintain the infrastructure required to extract, transform, load and enrich data from a variety of sources. With your help we’ll be able to get the right info, infer useful things and make better decisions. Then test, and keep improving.
When the warehouse is fully functional, you’ll lend your sharp logic to improve internal processes, automate systems, and optimise, well, everything. And down the track we’d love you to get involved with some Bayesian analysis, machine learning and other interesting data team projects.
If you get excited by the idea of providing the right data to inform great decisions; and you want that data to be accessible, understandable and trustworthy, then this could be the job for you. If you bring your experience, smarts and detail-oriented brain to help us, we’ll offer a world-class team to learn from, the tools you need to do your thing, and the support you need to flourish.
YOU COULD BE THE ONE, IF…
Your logic and reasoning is formidable, as is your determination. You are ordered and decisive, yet creative at the same time. You like things to end up fitting neatly in the boxes; but you don’t mind looking outside of them in the first place to find the answers. You get a kick out of getting things right, and you have the patience to do that every time. Because you present your work with pride, knowing you’ve done all you can to make sure it’s correct – and useful.
Disorder makes you uncomfortable. With well ordered data in a clean schema, life is good. But you love a challenge more than most other things, so where you see inconsistency or confusion, you also see an opportunity. And you’ll follow that thread until you’re confident you’ve sorted it out.
You might have been called a “bookworm” more than once in your life, because your curiosity has you forever seeking (and absorbing) information. And nowadays, this natural thirst for knowledge has you constantly looking at ways to improve, optimize and enhance – yourself, your processes, and your data. A bit like a mechanic will with a car, you’ll break apart the whole into pieces you can check and analyse, before rebuilding an idea, process or system into something better.
Sound familiar? If so, we’d love to meet you (and that brain of yours).
IF YOU WERE HERE IN THE FEW LAST WEEKS YOU MIGHT HAVE:
- Reviewed our overall data systems (supported by very competent sysadmins) to make sure everything was in order and to look for larger scale improvements
- Built out a handful of new pipelines to bring more of our core business data into our data warehouse
- Chased a handful of data validation alerts raised by our pipelines, and taken the time to get to the root cause of each of them, then either delegated the fix to an appropriate someone else or fixed them yourself
- Suggested an improvement to our A/B testing infrastructure
- Worked outside of data team, with our developers, flexing your database and query optimisation skills to decide whether to fix a performance issue they’re having at the database level, or insist that the fix should be in the code (and, that’s fun - they’re an excellent bunch)
- Provided an ad-hoc analysis (working with our analysts) to someone who requested it, integrating a one-off data source
- Talked with our CIO about some of our mid-term plans, and how we’ll support them with data
THESE ARE SOME QUALITIES YOU MUST POSSESS
- At least three years experience in data-related roles
- Advanced working knowledge of SQL and experience in ETL using a workflow management tool such as Apache Airflow
- Experience with building and optimising data pipelines
- Experience with collecting data from a variety of sources including APIs (good APIs, bad APIs, and ugly APIs)
- Strong analytical skills and an ability to perform root cause analysis
- Training in Computer Science, Statistics, Informatics, Information Systems or another relevant quantitative field (or demonstrable skill in one of those areas and the story of how you built that skill without formal training)
- Very high precision – you need to know how to verify that your work is correct
- Bonus points for more experience with relevant programming languages (ie. Ruby on RAILS, Python, R, Scala), PostgreSQL, project management and machine learning.