Data Analytics Engineer: Scalable DBT Pipelines (Remote)

N-iX

Zalasewo

On-site

PLN 150,000 - 230,000

Full time

14 days+
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Benefits offered by this job

Flexible working format
Competitive salary
Mentorship program
Tech talks and trainings

Job summary

N-iX in Poland is seeking a Middle Data Analytics Engineer to build reusable, production-grade pipelines powering large-scale data deals for AI labs. You’ll collaborate with BD, data science and engineering to translate customer requirements into scalable data solutions.

You will implement DBT models on Snowflake, optimize SQL queries, and participate in code reviews to maintain a robust data ecosystem. Flexible work options include remote, office-based or hybrid arrangements and opportunity for

Qualifications

  • Strong SQL background with an understanding of query optimization and Snowflake experience.
  • DBT experience preferred.
  • 3-5 years of experience in analytics/data engineering.
  • Perform code reviews and collaborate with the team to create an optimized ecosystem.

Responsibilities

  • Work with the BD team, data science and engineering to understand customer requirements and metadata.
  • Map requirements to existing metadata and apply data modelling to maximise reusability.
  • Build DBT models capable of querying up to 1B rows efficiently.
  • Refine DBT models based on visual QA for large-scale datasets.
  • Propose and implement automated solutions to streamline curation and scalability.
  • Serve as engineering point of contact to ensure timelines and clear requirements.

Skills

SQL
Data engineering
Analytics

Tools

DBT
Snowflake
BigQuery
Python
ClickHouse

Job description

N-iX in Poland is seeking a Middle Data Analytics Engineer to build reusable, production-grade pipelines powering large-scale data deals for AI labs. You’ll collaborate with BD, data science and engineering to translate customer requirements into scalable data solutions.

You will implement DBT models on Snowflake, optimize SQL queries, and participate in code reviews to maintain a robust data ecosystem. Flexible work options include remote, office-based or hybrid arrangements and opportunity for

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