Engineer II, Data Engineer

Overview

The Data Engineer II independently owns a data domain within Enterprise AI, designing pipelines for complex use cases, owning the quality of what digital workers deliver in that domain, and keeping its context accurate and audit-ready.

What you'll do

• Design pipelines for complex use cases and direct digital workers to build and operate them, with clear, defensible architectural trade-offs.
• Own the quality of agent-generated work in your domain: review, test and approve it within the remit EAI's operating model sets, and escalate what falls outside it.
• Improve how digital workers operate in your domain by refining the frameworks, tools and evaluations they use, iterating on reliability signals so manual intervention falls measurably over time.
• Own the context for your domain in the governed context layer: definitions, contracts, lineage and governance documentation.
• Contribute reusable components to the context layer, such as metadata enrichment, classification or lineage capture, that other domains can adopt.
• Build an end-to-end data quality framework for your domain, with lineage tracking and governance documentation that passes audit.
• Apply privacy and consent controls in AI data pipelines and manage PII appropriately across the data lifecycle.
• Design and build feature stores, vector databases or retrieval infrastructure for production AI systems, with data contracts that give each AI consumer consistent, quality-assured inputs.
• Manage training datasets, evaluation sets and data versioning for AI projects in production, and contribute to evaluation dataset design.
• Build cloud data infrastructure independently using infrastructure as code and contribute reusable components to the team's data platform.
• Design observability into pipelines from the start and resolve infrastructure issues with minimal disruption to consumers.
• Own incident response for your domain, with clear post-incident analysis and follow-through.
• Raise team technical quality through code review and documentation, with specific improvements to shared practices.
• Work closely with forward deployed engineers (FDEs) and AI engineering teams, translating ambiguous requirements into well-scoped designs and delivering data assets on time and to agreed quality standards.
• Contribute to design reviews with clear trade-off reasoning and communicate technical choices to engineering and non-technical stakeholders.

What you'll need

• 10+ years of experience building and operating production data pipelines and data models.
• Deep SQL and Python, with strong hands-on expertise in modern warehouses or lakehouses and in orchestration and transformation frameworks, such as Databricks, BigQuery, Airflow, dbt or Spark.
• Experience designing and building feature stores, vector databases or retrieval infrastructure for production AI systems, including data contracts for at least one AI consumer.
• Experience managing training datasets, evaluation sets and data versioning for at least one AI project in production.
• A track record of building data quality frameworks and lineage for a domain, and of applying privacy, consent and PII controls in AI data pipelines.
• Experience building cloud data infrastructure independently with infrastructure as code, with observability designed in from the start.
• Experience designing and operating at least one AI agent or LLM-powered tool inside a data workflow, and fluent, daily use of AI coding assistants and agents with sound judgement on what to accept, change or reject.
• Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience.

Nice to have

• Led the design and delivery of a component of a larger data platform.
• Experience with agentic systems in production: multi-step tool use, evaluations, guardrails and observability applied to operational data problems.
• Experience with quality frameworks and with catalogue, metadata or lineage tooling.
• Experience in regulated or high-stakes data environments, such as life sciences, finance or healthcare.

Details

• Location: Bengaluru Luxor North Tower.