is transforming meteorology by developing novel techniques for gathering and assimilating weather data into real-time analysis systems. Since real people will use these analyses to inform real decisions with major economic impacts, it’s imperative that we understand the quality and accuracy of our data.
As a Meteorological Data Validation Engineer, you’ll ensure that this data is always the highest quality possible. You’ll work across teams to help build systems to validate our new observations and forecasts against their traditional counterparts. You’ll also work to help investigate and analyze our weather data in comparison to any proprietary observations that clients might bring to the table. You’re always thinking about how we can analyze and demonstrate the accuracy of our data products, and when it comes to demonstrating their quality, you’re the first responder, always ready with a new analysis or visualization.
What You'll Be Doing
- Develop dashboards and other interactive tools to help directly evaluate our proprietary data products and to facilitate stakeholders across the company to play with and visualize our data and its accuracy
- Create continuous validation products which produce statistical analyses of our data against traditional sources, and proactively ensure that only the most accurate, highest-quality data reaches our API and clients
- Lead efforts to debug, analyze, and break down the root cause of quality issues when they arise, tracing data back through our internal data stores all the way to their sources
- Collaborate with the Customer Success and Product teams to help provide feedback to clients regarding our data quality
What You Bring
- Strong background (3+ years experience) in building data analysis and visualization pipelines, especially combining data from many different sources
- Experience scripting and automating data analyses and report generation, especially using the standard Python toolkit to call external APIs, process data, and possibly directly interact with raw scientific datasets
- Familiarity with traditional weather observation and forecast datasets, as well as sourcing them and working with their idiosyncrasies (e.g. file formats such as GRIB2, BUFR, and NetCDF)
- Excellent written and oral skills, particularly applied towards communicating complex, technical information to non-technical stakeholders
- Experience working on cloud computing systems, especially Amazon AWS or Google Cloud
- Knowledge of both traditional SQL and NoSQL databases
- Prior experience building analysis tools specifically aimed at weather observation and forecast datasets
- A BS in atmospheric science or any other field with some exposure to coursework in meteorology or the geosciences more generally