👋🏼 We're Nagarro. We are a digital product engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (18 000+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! By this point in your career, it is not just about the tech you know or how well you can code. It is about what more you want to do with that knowledge. Can you help your teammates proceed in the right direction? Can you tackle the challenges our clients face while always looking to take our solutions one step further to succeed at an even higher level? Yes? You may be ready to join us.

We are looking for a Senior Data Engineer with strong expertise in DBT and modern data stack technologies.

• Lead the design, development, and implementation of data models using DBT.
• Own and drive DBT best practices (modularization, testing, documentation, performance optimization).
• Translate business requirements into scalable and efficient data models.
• Collaborate with data engineers, analysts, and stakeholders across the organization.
• Ensure data quality and reliability through robust testing and validation frameworks.
• Optimize SQL queries and DBT pipelines for performance and scalability.
• Manage deployment workflows, CI/CD pipelines, and version control (Git).
• Troubleshoot and resolve data pipeline and transformation issues.
• Mentor and guide team members on DBT and modern data engineering practices.

• 6+ years of hands-on DBT experience
• Experience with both dbt Core and dbt Cloud.
• Strong experience with Jinja templating
• Ability to build reusable macros and logic
• Materializations: incremental, snapshot, view, table, ephemeral.
• Experience defining and implementing: generic and singular tests.
• Familiarity with packages like: dbt-utils, dbt-expectations, Elementary.
• Experience building and owning data models across the full lifecycle.

• Strong problem-solving and analytical skills.
• Experience working in enterprise environments.
• Familiarity with:
  • Git.
  • AWS MWAA (Airflow).
  • Amazon Redshift.
  • Modern data platform tooling.