Data Analytics Engineer, Health Strategic Initiatives
Santa Clara Valley (Cupertino), California, United States
Software and Services
Have you ever wanted to work on something that really matters? Is it important to you to help others live longer, more fulfilling lives? The Health Strategic Initiatives team is focused on just that — enabling individuals to live a healthier, happier life through personalized and compelling products. We are an experienced team of business leaders, doctors, designers, PMs, and data scientists. We work in a collaborative and dynamic environment where we are constantly pushing ourselves to redefine the industry and create delightful user experiences. Data is central to the success of our team. We work in a tight feedback loop where data insights drive feature development and design as well as defining future strategy and products. As a behavioral data scientist on the team you will explore behavior change, causal impact of product features on outcomes, incentives, and other behavior related questions across the various programs we have launched.
- Experience implementing data transformation using Python and Pandas
- Experience with Unix-based command line interface and Bash scripts
- Extract Transform Load (ETL) experience using Spark, Hadoop, or similar technologies
- Experience with workflow scheduling / orchestration such as Airflow or Oozie
- Experience with query APIs using JSON, ProtocolBuffers, or XML
- Data visualization experience using Python, Tableau, R, Metabase, Superset, etc.
- Database development experience with Relational or MPP/distributed systems such as Oracle/Teradata/Vertica/Hive a plus
As a data analytics engineer you will partner closely with data scientists to deliver accurate and timely insights. Your work will be foundational to analytics and data science performed by the team. A few of your day to day roles will include QA and monitoring of raw and aggregate data, aggregating raw data, automating aggregates, and supporting visualization and reporting by identifying and deploying meaningful data pipelines.
Education & Experience
Bachelors in Computer Science, Mathematics, or similar quantitative field with a minimum of 3 years professional experience; Masters preferred