Senior Data Engineer - Internal Data Platform & Analytics

Overview

Build and operate Glean’s internal data platform as an individual-contributor Data Engineer. The role focuses on analytics engineering for internal teams, including reliable, governed, cost-efficient data infrastructure and analytics foundations, and is not customer-facing implementation.

What you'll do

• Build and maintain reliable batch and API-based data ingestion pipelines.
• Improve data quality through testing, continuous integration (CI) checks, ownership metadata, and clear layer boundaries.
• Operate and improve BigQuery data infrastructure with an emphasis on performance and cost efficiency.
• Implement data access controls, governance workflows, and safe self-serve access patterns.
• Improve pipeline observability, failure classification, incident triage, and recovery processes.
• Partner with Data Science, Business Intelligence, Finance, Sales Operations, Marketing, Security, Reliability Engineering, and other internal teams to understand data needs and deliver reusable platform capabilities.
• Participate in design reviews, code reviews, documentation, and operational support for the data platform.

What you'll need

• Minimum 7–10 years overall, including at least 7 years of data engineering experience.
• Strong Data engineering fundamentals and experience building production data systems.
• An exceptionally high AI proficiency through habitual, high-value use of LLMs; sound judgment about when and how to apply them; rigorous validation and workflow improvement.
• Experience with SQL and Python, or comparable programming languages.
• Experience with a cloud data warehouse, preferably BigQuery or a similar platform.
• Experience with data transformation frameworks such as DBT, including testing and deployment workflows.
• In Depth Understanding of Columnar File systems like parquet, Hudi Or Iceberg.
• Understanding of dimensional modeling, data contracts, lineage, and data quality practices.
• Experience designing or operating APIs, batch pipelines, or event-driven ingestion systems.
• Ability to communicate technical trade-offs clearly and work effectively with internal stakeholders.
• Ownership mindset: you can take a problem from discovery through implementation, rollout, and operational follow-through.
• Ability to maintain a productive collaboration between IST and US PST time zones.

Nice to have

• Experience with BigQuery governance, IAM/RBAC, policy tags, masking, streaming systems or cost controls.
• Experience building reusable data platform frameworks rather than one-off pipelines.
• Familiarity with semantic layers, metric stores, or systems that make trusted data consumable by AI and analytics tools.
• Experience with data observability, orchestration, CI/CD, or infrastructure-as-code.
• Experience working in a fast-growing company where requirements and priorities evolve quickly.

Details

• Location: Bangalore, India.
• This is an in-person role based in Bangalore, India, with regular office presence expected.
• This role is hybrid, with 4 days a week in the Bangalore office.