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Senior Data Engineer, Internal Data Platform & Analytics

Glean· Data
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Hybrid (Bangalore)Full-timePosted 2w ago

About the role

Senior Data Engineer role focused on building and operating Glean’s internal data platform for analytics across internal teams. In-person role based in Bangalore, hybrid (4 days/week in office).

Responsibilities

  • Build and maintain reliable batch and API-based data ingestion pipelines.
  • Improve data quality through testing, CI checks, ownership metadata, and clear layer boundaries.
  • Operate and improve BigQuery data infrastructure with 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 internal teams (Data Science, BI, Finance, Sales Operations, Marketing, Security, Reliability Engineering) to understand data needs and deliver reusable platform capabilities.
  • Participate in design reviews, code reviews, documentation, and operational support for the data platform.

Qualifications

  • 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.
  • High proficiency with AI via LLMs; sound judgment and rigorous validation.
  • Experience with SQL and Python (or comparable languages).
  • Experience with a cloud data warehouse (preferably BigQuery).
  • Experience with DBT and testing/deployment workflows.
  • In-depth understanding of columnar file formats (Parquet, Hudi, Iceberg).
  • Understanding of dimensional modeling, data contracts, lineage, and data quality practices.
  • Experience designing or operating APIs, batch pipelines, or event-driven ingestion systems.
  • Strong communication of technical trade-offs with stakeholders.
  • Ownership mindset from discovery to rollout and operation.
  • Ability to collaborate across 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.
  • Familiarity with semantic layers, metric stores, or systems making trusted data consumable by AI/analytics.
  • Experience with data observability, orchestration, CI/CD, or infrastructure-as-code.
  • Experience working in fast-growing company environments.

Skills

Required:Data ingestion pipelinesData qualityBigQueryData governanceObservability & incident responseLeadership & collaboration
Last updated Oct 21, 2026. Interested? Apply on the company site.

About Glean

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