1 month ago
Bengaluru, IndiaSenior
Responsibilities
- Build and maintain reliable batch- and API-based data ingestion pipelines.
- Improve data quality through testing, CI checks, ownership metadata, and clear data-layer boundaries.
- Operate and optimize BigQuery infrastructure for performance and cost efficiency.
- Implement data access controls, governance workflows, and safe self-service access patterns.
- Improve pipeline observability, failure classification, incident triage, and recovery processes.
- Partner with internal teams to understand data needs and deliver reusable data-platform capabilities.
- Participate in design reviews, code reviews, documentation, and operational support.
Requirements
- 7–10 years of overall experience, including at least 7 years of data engineering experience.
- Strong data engineering fundamentals and experience building production data systems.
- High proficiency in using LLMs with sound judgment, 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 dbt or comparable data transformation frameworks, including testing and deployment workflows.
- In-depth understanding of columnar file systems such as 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.
- 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.
- Clear communication of technical trade-offs, effective stakeholder collaboration, end-to-end ownership, and ability to collaborate across IST and US Pacific time zones.
- Experience working in a fast-growing company with evolving requirements and priorities.
Benefits
- Hybrid/in-person Bangalore role with four days per week in the office.
- Certain roles may be eligible for variable compensation, equity, and benefits.
- The role includes collaboration across IST and US Pacific time zones.
About Glean
Glean.ai is Intelligent AP. We leverage untapped invoice data to surface relevant context, actionable insights, and savings recommendations that power great spend decisions.