Data Engineer Lead
We’re on a mission to make knowledge work faster and more humane. We believe that AI will fundamentally transform how people work. In the future, everyone will work in tandem with expert AI assistants who find knowledge, create and synthesize information, and execute work. These assistants will free people up to focus on the higher-level, creative aspects of their work
We’re building a system of intelligence for every company in the world. On the surface, you can think of it as Google + ChatGPT for the enterprise. Under the hood, our platform is the connective tissue between AI and knowledge. It brings all of a company’s knowledge together, understands it at a deep level, provides industry-leading search relevance over it, and connects it to generative AI agents and applications
Glean was founded by a seasoned team of former Google search and Facebook engineers who saw a need in the enterprise space for their technical depth and passion for AI. We’re a diverse team of curious and creative people who want to help each other get big things done—so we can help other teams do the same.
We're backed by some of the Valley's leading venture capitalists—including Sequoia, Kleiner Perkins, Lightspeed, and General Catalyst—and have assembled a world-class team with senior leadership experience at Google, Slack, Facebook, Dropbox, Rubrik, Uber, Intercom, Pinterest, Palantir, and others.
About the roleGlean is building a world-class Data Organization composed of data science, applied science, data engineering and business intelligence groups. Our data engineering group will be based in our Bangalore, India office. We are hiring our first data engineer. In this role, you will:
- Start as a fully hands-on individual contributor, and transform into a mostly hands-on tech lead management role as you build Glean’s data engineering functionality.
- Help improve the availability of high-value upstream raw data by
- channeling inputs from data science and business intelligence to identify biggest gaps in data foundations
- partnering with Product Engineering teams as they craft product logging initiatives & processes
- partnering with Go-to-Market & Finance operations groups to create streamlined data management processes in enterprise apps like Salesforce, Marketo and various accounting software
- Architect and implement key tables that transform structured and unstructured data into usable models by the data, operations, and engineering orgs.
- Ensure and maintain the quality and availability of Glean’s data within reasonable SLAs
- Own and improve the reliability, efficiency and scalability of ETL tooling, including but not limited to dbt, BigQuery and Metabase
- Partner with Business Intelligence to improve the reliability, scalability and usability of our business intelligence & visualization tools like Metabase for Data, product, engineering and operations teams.
- Implement and disseminate developer-friendly best practices for our data stack to ensure that data, operations, and engineering can efficiently write source-controlled and adhoc SQL code and other ETL jobs.
You will thrive at this role if:
- You have 8+ yrs of work experience in data engineering /software engineering as a bachelor degree holder. This requirement is 7+ for masters degree holders and 5+ for PhD Degree holders.
- You have 1+ year of tech lead management experience and have mentored several data engineers before.
- You are so proficient in SQL that you’re able to up-level other SQL users around you.
- You are proficient in Python
- You have experience with BigQuery and dbt
- You are concise and precise in written and verbal communication. Technical documentation is your strong suit.
- You have experience working with a large array of cross-functional partners ranging from product and engineering/research to go-to-market and finance
- You have experience working with stakeholders and peers in different time zones
You are a particularly good fit if:
- You have experience with Salesforce, Marketo, and Google Analytics.
- You have experience in distributed data processing & storage, e.g. HDFS
- You have experience in data privacy, e.g. data access governance.
- You have experience forming the data engineering charter in a startup
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.