Data Analytics Engineer: Scalable DBT Pipelines

N-iX; Kraków, Wrocław, Warszawa; On-site; PLN 120,000 - 180,000; Full time

Job summary

N-iX is seeking a Middle Data Analytics Engineer to build reusable, production-grade pipelines powering large-scale curated training sets for leading AI labs. You will ship engineering solutions with immediate revenue impact and collaborate with some of the world’s largest AI companies.

You will work with BD, data science, and engineering teams to understand requirements, map metadata, and develop scalable DBT models that can query billions of rows, while applying robust data modelling practices.

Qualifications

• Strong SQL background and knowledge of query optimization.
• DBT experience preferred.
• Excellent communication skills.
• 3-5 years of analytics/data engineering experience.
• Collaborative, cross-team mindset and ability to review code.

Responsibilities

• Collaborate with BD, data science, and engineering teams to understand requirements.
• Map requirements to metadata and apply data modelling for reusability and scalability.
• Build DBT models capable of querying up to 1B rows efficiently.
• Refine DBT models based on visual QA for accuracy at scale.
• Propose automated solutions to streamline curation and increase scalability.
• Serve as engineering point of contact to manage timelines and technical implementation pieces.
• Expand data curation workflow to support data science approaches within DBT and enhance testing.

Skills

SQL

Communication

Analytics

Code Reviews

Tools

Snowflake

DBT

BigQuery

Python

ClickHouse

Job description

N-iX is seeking a Middle Data Analytics Engineer to build reusable, production-grade pipelines powering large-scale curated training sets for leading AI labs. You will ship engineering solutions with immediate revenue impact and collaborate with some of the world’s largest AI companies.

You will work with BD, data science, and engineering teams to understand requirements, map metadata, and develop scalable DBT models that can query billions of rows, while applying robust data modelling practices.