Full-Stack Data Engineer / Analytics Engineer
We are looking for someone who can help mature our existing data applications and innovate new use cases. Currently we have many different sensors and pipelines to expose their data in data lake/data warehouse. We run BI queries on top of that data and have Spark jobs into RDS to expose them to specific use-cases.
We have some data science applications as well. There’s many obvious machine learning use-cases that we also haven’t yet explored but would like to.
We’re looking for someone who can act as a leader in our product team and help build and fulfill the vision.
- Design and implement end-to-end data pipelines, and work closely with stakeholders to build instrumentation and define data models
- Take ownership of monitoring to ensure high availability of our data tooling
- Build actionable production-quality internal dashboards, with well defined KPI’s
- Work with the Cloud team to create customer-focused dashboards to help customers understand their WalletConnect usage.
- Partner closely with product, engineering and other business stakeholders to influence product and business decisions with data
- Influence leadership to drive more data-informed decisions
- 3+ years of experience as a Data engineer/scientist.
- Extensive experience with Python/Spark/databases
- Deep understanding of advanced SQL techniques, dimensional modeling and scaling ETL pipelines
- Experience with applied statistics and quantitative modeling
- Demonstrated knowledge in monitoring data systems
Nice to have:
- Domain experience in crypto and SaaS would be a plus
- Knowledge of Rust and TypeScript (help on data ingestion pipeline)
- Demonstrated ability to translate analytical insights into clear recommendations and effectively communicate them to technical and non-technical stakeholders
- Strong background in statistical modeling such as regression, survival and cohort analysis, time series forecasting, etc.
- Experience in the AWS Glue/Athena toolsuite, Spark, Presto, DBT
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