Join Glean: Data Engineer Lead Position

About Glean

At Glean, our mission is to expedite knowledge work, making it more humane and efficient. We envision a future where AI transforms workflow dynamics, allowing AI assistants to handle knowledge retrieval, information synthesis, and task execution. This transformation will enable people to focus on higher-level, creative aspects of their work.

We are developing an intelligence system for every company worldwide. Think of it as Google + ChatGPT for enterprises. Our platform acts as a bridge, connecting AI and knowledge. It aggregates a company's information, deeply understands it, ensures top-notch search relevance, and connects it to generative AI agents and applications.

Founded by ex-Google and Facebook engineers, Glean leverages deep technical expertise and a passion for AI to meet the needs of the enterprise sector. We are a diverse team committed to helping each other achieve remarkable goals, so we can enable other teams to do the same.

We're backed by top-tier venture capitalists like Sequoia, Kleiner Perkins, Lightspeed, and General Catalyst. Our team includes senior leaders from Google, Slack, Facebook, Dropbox, Rubrik, Uber, Intercom, Pinterest, Palantir, and more.

Data Engineering Role: Data Engineer Lead

Glean is building a premier Data Organization comprising data science, applied science, data engineering, and business intelligence groups. Our data engineering team will be based in Bangalore, India. We are hiring our inaugural data engineer. In this role, you will:

• Begin as a hands-on individual contributor. Demonstrate high-quality execution and leadership skills to evolve into forming Glean’s first data engineering group within the Data org.
• Enhance high-value upstream raw data availability by:
  • Channeling inputs from data science and business intelligence to identify data foundation gaps
  • Collaborating with Product Engineering on product logging initiatives and processes
  • Partnering with Go-to-Market & Finance operations to streamline data management in enterprise apps like Salesforce, Marketo, and accounting software
• Architect and implement key tables to transform structured and unstructured data into usable models for data, operations, and engineering.
• Maintain and ensure data quality and availability within reasonable SLAs.
• Enhance the reliability, efficiency, and scalability of ETL tools, including dbt, BigQuery, Metabase.
• Collaborate with Business Intelligence to improve the reliability, scalability, and usability of business intelligence & visualization tools like Metabase for Data, product, engineering, and operations teams.
• Implement developer-friendly best practices for our data stack, ensuring efficient code writing for data, operations, and engineering teams.

Key Qualifications

Candidates will excel in this role if they:

• Hold 8+ years of experience in data/software engineering (7+ for master's degree holders, 5+ for PhD degree holders).
• Possess 1+ year of tech lead management experience and have mentored data engineers.
• Are proficient in SQL and able to set best practices, improving the organization's SQL user base.
• Have expertise in Python, Java, or Golang.
• Have experience with cloud-based data tools like BigQuery and dbt.
• Are skilled with large-scale data processing tools such as Beam and Spark.
• Know data pipelining tools like Apache, Stitch, Hevo Data, and Fivetran.
• Are familiar with cloud computing services like GCP and/or AWS.
• Have strong written and verbal communication skills, especially in technical documentation.
• Have experience working with a diverse array of cross-functional partners.
• Have experience with stakeholders and peers across various time zones.

Preferred Qualifications

Candidates are particularly suited if they:

• Have experience with Salesforce, Marketo, and Google Analytics.
• Understand distributed data processing & storage, such as HDFS.
• Are knowledgeable in data privacy and data access governance.
• Have experience defining the data engineering charter in a startup.