N
Nagarro
Data Engineer
Staff Engineer - Data Engineer
On-siteStaffData Engineerposted 1w ago
Role summaryAI-generated
This staff-level data engineer will lead production dbt pipelines, designing complex SQL transformations and ensuring data quality across cloud platforms. The role requires deep expertise in dbt, Snowflake, Databricks, BigQuery, or Redshift, and daily use of Claude Code or GitHub Copilot for coding tasks.
Skills required
About this role
- 6+ years of experience in Data Engineering, Analytics Engineering, or related fields.
- 3+ years of hands-on experience with dbt in production environments.
- Strong expertise in SQL and complex data transformation development.
- Strong understanding of dbt Core and/or dbt Cloud.
- Experience with dbt, including
- dbt models and materialization
- Incremental models
- Macros and Jinja
- dbt tests and data quality frameworks
- Snapshots
- Seeds and sources
- Documentation and lineage
- dbt packages
- Strong experience with at least one cloud data platform, such as:
- Snowflake
- Databricks
- BigQuery
- Amazon Redshif
AI skills (required for all roles)
- Daily, fluent use of Claude Code and/or GitHub Copilot for implementation, refactoring, test generation, and code review
- Ability to establish team standards for AI-assisted development: effective prompting, trust-vs-verify discipline on generated code, security/IP guardrails, and reviewing AI-authored changes
- Working understanding of LLM fundamentals: context windows, tokens, model selection, and prompt/context engineering
- Experience integrating AI into developer workflows and agentic/automation tooling (MCP servers, AI-driven CI steps, codegen and doc-generation pipelines)
- Able to evaluate AI tooling pragmatically: measuring real productivity and quality impact, not hype
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