We are looking for an experienced leader in data and analytics to build the team that will enable the rest of the business to make better decisions. Reporting to the VP of Operations, you will take over all data engineering, integrity, and management for our cloud product data, our on-premises product data, and our marketing and business data. You will also build and run our analytics and data science team, being responsive to needs from across the business and proactive in identifying opportunities for improvement.
Within one month, you will…
Study and become an expert in Sourcegraph’s products, customers, business model, and our values
Get to know the rest of the BizOps and Data teams, and meet your counterparts across the rest of the organization in Product, Engineering, Sales, Marketing, and more
Shadow members of the team as they fulfill ad hoc data requests (e.g. “why did MAUs spike in June and fall back in July?”), run proactive analyses (e.g. “what user actions drive retention?”), and execute larger projects (e.g. a migration of ETL jobs from BigQuery to Dbt)
Identify key team needs and work with the head of Operations to do team capacity and headcount planning.
Within three months, you will…
Complete an audit of our existing product and marketing data pipelines, and work with the team to build a plan to address near-term pains and long-term architecture planning.
Become comfortable with our end-user analytics tools (Looker, Amplitude) and begin to think through the model to support the rest of the company via end user training, increased self-service usage, and analytics team support prioritization
Be interviewing candidates to fill key roles on the team.
Within six months, you will…
Be a trusted advisor to leadership across the company on analytical matters
Be tracking team key performance indicators, such as data pipeline SLAs, request response and resolution time, percentage of requests self-serviced, and more
Have established a culture on the analytics team of being more proactive and less reactive
Be in process of building a team, systems, and processes that can support the business as it grows by multiples in the coming years
Hands-on experience in data engineering (building and managing large-scale data pipelines, data transformations/ETLs, data modeling for end users, etc.)
Demonstrated experience in an analytics role and an understanding of data science; deep familiarity with SQL, and experience with Python, R, Julia, or another data science language
A strategic point of view and a strong perspective on the principles of an effective data strategy
Leadership experience in an analytical role at a growth-stage enterprise SaaS company
Nice to haves
Experience with our existing stack: Google Cloud Platform (PubSub/DataFlow), Google BigQuery, Looker, Amplitude, Google Analytics