Staff Data Engineer

About Glean:

Founded in 2019, Glean is an innovative AI-powered knowledge management platform designed to help organizations quickly find, organize, and share information across their teams. By integrating seamlessly with tools like Google Drive, Slack, and Microsoft Teams, Glean ensures employees can access the right knowledge at the right time, boosting productivity and collaboration. The company’s cutting-edge AI technology simplifies knowledge discovery, making it faster and more efficient for teams to leverage their collective intelligence.

Glean was born from Founder & CEO Arvind Jain’s deep understanding of the challenges employees face in finding and understanding information at work. Seeing firsthand how fragmented knowledge and sprawling SaaS tools made it difficult to stay productive, he set out to build a better way - an AI-powered enterprise search platform that helps people quickly and intuitively access the information they need. Since then, Glean has evolved into the leading Work AI platform, combining enterprise-grade search, an AI assistant, and powerful application- and agent-building capabilities to fundamentally redefine how employees work.

About the Role:

Glean is building a world-class Data Organization composed of data science, applied science, data engineering and business intelligence groups. Our data engineering group is based in our Bangalore, India office. In this role, you will work on customer-facing and Glean employee-facing analytics initiatives:

Customer-facing analytics initiatives: Customers rely on in-product dashboards and if they have the willingness and resources, self-serve data analytics to understand how Glean’s being used at their company in order to get a better sense of Glean’s ROI and partner with Glean to increase user adoption. 

You’re expected to partner with backend and data science to maintain and improve the data platform behind these operations

• reflect usage on new features
• reflect changes on the underlying product usage logs on existing features
• identify and close data quality issues, e.g. gaps with internal tracking, and backfill the changes
• triage issues customers report to us within appropriate SLAs
• help close customer-facing technical documentation gaps 

You will:

• 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 Go-to-Market & Finance operations groups to create streamlined data management processes in enterprise apps like Salesforce, Marketo and various accounting software
• partnering with Product Engineering teams as they craft product logging initiatives & processes
• 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 internally used tables within reasonable SLAs
• Own and improve the reliability, efficiency and scalability of ETL tooling, including but not limited to dbt, BigQuery, Sigma. This includes identifying implementing and disseminating best practices as well.

About you:

• You have 9+ yrs of work experience in software/data engineering (former is strongly preferred) as a bachelor degree holder. This requirement is 7+ for masters degree holders and 5+ for PhD Degree holders.
• You’ve served as a tech lead and mentored several data engineers before.
• Customer-facing analytics initiatives:
  • You have experience in architecting, implementing and maintaining robust data platform solutions for external-facing data products.
  • You have experience with implementing and maintaining large-scale data processing tools like Beam and Spark.
  • You have experience working with stakeholders and peers from different time zones and roles, e.g. ENG, PM, data science, GTM, often as the main data engineering point of contact.
• Internal-facing analytics initiatives:
  • You have experience in full-cycle data warehousing projects, including requirements analysis, proof-of-concepts, design, development, testing, and implementation
  • You have experience in database designing, architecture, and cost-efficient scaling
  • You have experience with cloud-based data tools like BigQuery and dbt
  • You have experience with data pipelining tools like Airbyte, Apache, Stitch, Hevo Data, and Fivetran
• General qualifications:
  • You have a high degree of proficiency with SQL and are able to set best practices and up-level our growing SQL user base within the organization
  • You are proficient in at least one of Python, Java and Golang.
  • You are familiar with cloud computing services like GCP and/or AWS.
  • You are concise and precise in written and verbal communication. Technical documentation is your strong suit. 
• You are a particularly good fit if:
  • You have 1+ years of tech lead management experience. Note this is distinct from having a tech lead experience, and involves formally managing others.
  • You have experience working with customers directly in a B2B setting.
  • You have experience with Salesforce, Marketo, and Google Analytics.
  • You have experience in distributed data processing & storage, e.g. HDFS

Location:

• This role is hybrid (3 days a week in our Bangalore office)

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.