Why this role stands out
As a Senior Data Engineer at Glean, you'll build and scale the internal data platform that powers their innovative Work AI. This hybrid role is perfect for experienced engineers eager to shape impactful data solutions within a rapidly growing, award-winning company. You'll have ample opportunity to develop your skills and contribute to a cutting-edge technology environment.
Quick overview
Job description
- 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.
- Minimum experience: 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
- 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.
- This role is hybrid (4 days a week in our Bangalore office)
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