Data & Analytics Engineer (Python / dbt / GCP)

20k - 25k PLN20 000 - 25 000 PLN/ mies./ mies.

NieokreśloneZdalnieFull-time

#460069·Dodano 6 dni temu·1

Źródło: LinkGroup

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Tech Stack / Keywords

PythondbtSQLGoogle Cloud Platform (GCP)Google LookerInformaticaBigQuery machine learning

Podsumowanie oferty

The role combines analytics engineering, data integration, and Python-based AI/ML development. You will build analytical data models and pipelines, integrate data from platforms including Informatica, and support analytics and AI/ML workloads using Python, dbt, and Google Cloud Platform (GCP).

Wymagania

Proven experience in data engineering, analytics engineering, or a similar role.
Strong Python and SQL skills.
Hands-on experience with dbt and data transformation.
Experience with data modeling and semantic layer concepts.
Familiarity with Google Looker or similar business intelligence and analytics tools.
Experience with data integration, extraction, and processing from multiple sources.
Knowledge of Informatica or experience working with data originating from Informatica-based platforms.
Understanding of machine learning and AI engineering concepts, with practical experience developing Python-based solutions.
Familiarity with cloud-based data platforms, preferably Google Cloud Platform (GCP).
Ability to work independently across different areas of the data lifecycle.

Nice to have:

Experience with BigQuery and Google Cloud data services.
Experience developing and deploying ML/AI solutions in a cloud environment.
Familiarity with data orchestration tools and modern data stack architectures.
Experience building reusable semantic models and standardized business metrics.

Obowiązki

Design, develop, and maintain analytical data models and transformation workflows using dbt.
Build and maintain semantic models and support analytics and reporting solutions using Google Looker.
Develop data integration and processing solutions using Python.
Extract, transform, and integrate data from Informatica and other source systems.
Build, maintain, and optimize data pipelines to ensure data quality, reliability, and consistency.
Contribute to machine learning and AI engineering initiatives, including developing Python-based solutions.
Use Google Cloud Platform services to support data processing, analytics, and AI/ML workloads.
Collaborate with data engineers, analysts, and business stakeholders to translate business needs into scalable technical solutions.
Apply best practices in data modeling, testing, documentation, version control, and performance optimization.

Benefity

The opportunity to work across analytics engineering, data integration, and AI/ML.
Exposure to modern data technologies and cloud-based solutions.

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