Senior Business Intelligence Engineer, Data Science - Location Flexible
San Francisco, CA; Remote - US
Role Description The Business Intelligence team sits at the intersection of numerous cross-functional partnerships including (but not limited to) Product, Growth, Marketing, Sales, Business Development, Data Engineering, and Data Science. We wear multiple hats and flex multi-disciplinary skillsets in order to deliver repeatable and scalable data solutions to support better decision making throughout Dropbox. Our products impact a wide audience, ranging from non-technical to technical, from the individual contributor to the C-Suite. We are seeking a Senior Business Intelligence Engineer to own key business partnership from end-to-end. You are not simply a dashboard developer. You are an internal consultant who will embed within partner teams to diagnose their pain points and meticulously craft a data strategy to improve their insights capabilities. Successful candidates will have:
- A passion for creating accessible and intuitive data models. Knowledge of data warehouse modeling best practices and tradeoffs (dimensional data modeling, Kimball, Inmon, etc.).
- An obsession with data quality and cleanliness. Even a 1% variance keeps you up at night.
- An expertise in data visualization best practices, understanding the right design approach to use for a given audience.
- Customer obsession and accountability to partners. Their problems are your problems.
- Creation of semantic layers in the data warehouse that abstract complex business concepts.
- Data governance and certification of sources of truth for key data sets at Dropbox.
- Consulting on development of new data sets, being the voice of the customer/business by partnering with Data Engineering and Data Scientists to build the right pipelines.
- Maintenance and stewardship of metric definitions, KPIs, customer segmentations, etc.
- Development of automated dashboards and reports to support a variety of use cases from business reviews to exploratory analyses.
- Develop alerting mechanisms to separate the signal from the nose.
- Identify and analyze key trends to communicate to senior leaders.
- SQL as a first language with the chops to go toe-to-toe with any data engineer.
- The ability to develop and automate their own ETL. Proficiency in programming/scripting in Python, Airflow, and/or Stored Procedures is a plus.
- An expertise in one or more industry leading enterprise business intelligence tools such as Tableau, Looker, PowerBI, Qlik, etc. (Tableau preferred) ..as well as the basics like Excel.
- Experience working across both Hadoop (Hive) and traditional RDBMS (Snowflake, Teradata, etc.) environments on high volume customer data sets relating to finance, subscriptions, product usage and engagement.
- An ability to analyze key trends and communicate insights, as well as the ability to develop/innovate new metrics to track the business.
- An ability to translate business requirements into technical requirements and vice versa.
- Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- 3+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
- Strong project management and prioritization skills
- Strong verbal and written communication skills
Job tags: Airflow Business Intelligence Consulting Economics Engineering ETL Finance Hadoop Looker Marketing PowerBI Python SQL Tableau
Job region(s): North America Remote/Anywhere
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