Senior Data Engineer - Internal Data Platform & Analytics
AI in this role
- 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)
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.
How we rate this
Senior Data Engineer - Internal Data Platform & Analytics at Glean Work rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI Agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get a free CV reviewGet new data engineer jobs (Works on AI ●●●○ or higher) by email
One email a week with the new data engineer jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Data roles that work on AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step