Why This Job is Featured on The SaaS Jobs
This Tech Lead Manager role sits at a core SaaS intersection: turning product usage data into customer facing analytics and internal decision support. The remit spans an external data platform that powers in product dashboards and self serve reporting, alongside analytics engineering that strengthens how teams consume data across the business. That blend is increasingly central in enterprise oriented SaaS, where instrumentation, data quality, and trust in metrics directly shape adoption and billing models.
From a career perspective, the position offers a rare dual track in SaaS data leadership. It combines formal people management with hands on ownership of pipelines, warehousing, and reliability practices, while partnering closely with backend, data science, and go to market systems. Experience here tends to translate across modern SaaS orgs because it touches common patterns such as consumption based billing signals, SLAs for data products, and governance of shared datasets used by multiple functions.
This role is best suited to an experienced data engineer who wants to remain technical while taking accountability for a team’s direction and stakeholder alignment. It will appeal to professionals comfortable being the primary data engineering interface for non specialists, and who prefer work that alternates between deep platform building and pragmatic issue triage driven by customer needs.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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 entirely based in our Bangalore, India office.
Glean data engineering has two mandates:
1-) our customer-facing data platform akin to a data platform software ENG team
2-) analytics engineering to enable our other internal SQL/pipeline/BI tool developers horizontally.
In this role, you’ll serve as a tech lead manager for Glean’s one and only data engineering team:
- ~30% of your time will go into supporting senior-level data engineers to help grow them from a technical & career perspective.
- ~70% of your time will go into hands on work in the following areas:
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. Since we work with increasingly large enterprises spending large resources with Glean, our customer-facing data platform is a major platform for our enterprise-grade AI posture.
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
- Consumption-based billing
- 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
Glean employee-facing analytics initiatives:
- Help improve the availability of high-value upstream data data in 3rd party apps by
- channeling inputs from 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
- 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.
You will:
- 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 12+ yrs of work experience in software/data engineering (former is strongly preferred) as a bachelor degree holder.
- 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.
About you:
- 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
- You have experience with cross-function collaboration with US partners.
- You’re comfortable reporting to org leaders who themselves are not data engineers. This is a role where you represent Glean’s only data ENG team.
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.
