||We are looking for a dynamic Data Scientist / Analytics Engineer to join the Data Foundations team. In Data Foundations, we build solutions that impact hundreds of engineers and data scientists, thousands of daily data processing jobs and ultimately the experience of hundreds of MILLIONS of users, via more data-informed recommendations and user experience!
You will work in our Insights team, alongside other Data Scientists and User Researchers supporting a talented group of engineers and product managers to help us better understand how our internal customers interact with our data products and services.
What you’ll do
* Apply rigorous analysis to understand and document complex workflows, data flows and processes.
* Work with our stakeholders to define metrics and identify opportunities to measure outcomes.
* Work closely with our team of Data Scientists to craft data structures and pipelines, which will empower research and analysis.
* Develop high-impact dashboards to visualise usage patterns and data flows within our data ecosystem
* You will be a primary contributor to the analytics data layer of our team’s data environment, enabling easy access to standardised, high quality data.
Who you are
* At least 3 years of experience in a similar role working with large scale data, using both SQL and Python, in a professional setting.
* Significant experience in designing analytical data layers and in conducting ETL with large and complex data sets.
* Knowledgeable in data modeling, data access and data storage techniques.
* Experienced with SQL-based nested data structure manipulation, windowing functions, query optimization, data partitioning techniques, etc.
* Knowledge of Google BigQuery optimization is a plus.
* Able to design compelling visualizations of data, ideally in Tableau.
* Familiar with product metrics and reporting.
* A communicative person who builds strong relationships with colleagues and partners. You are independent and comfortable with ambiguity and complexity.
* Background in computer science, engineering, physics, statistics, economics, mathematics, or similar quantitative discipline or comparable experience.