Data Engineer (DBX, dbt), Senior

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SeniorHybryda·WarsawFull-time

#468208·Dodano 2 dni temu·0

Źródło: Webellian

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Tech Stack / Keywords

DatabricksdbtPython PySpark SQL Microsoft Azure GitHub TerraformdltHubPower BI

Podsumowanie oferty

Join a large-scale data transformation project for a leading insurance company, building a Central Data Platform that integrates data from multiple sources for analytics and reporting. You will design scalable data architecture and reliable pipelines using Databricks, Python, PySpark, and dbt.

Wymagania

Proven senior-level experience in Data Engineering, Data Architecture, or a similar role.
Strong hands-on experience with Databricks.
Advanced knowledge of Python and practical experience with PySpark.
Strong experience designing and optimizing ETL and ELT pipelines.
Very good knowledge of SQL and relational databases.
Experience in data architecture, data modelling, and scalable data platform design.
Practical experience with dbt.
Experience with Microsoft Azure or other cloud-based data platforms.
Knowledge of CI/CD practices and tools, particularly GitHub.
Understanding of cloud infrastructure, orchestration, deployment, and data security.
Ability to translate complex requirements into scalable technical solutions.
Experience working in large, distributed, or multi-team environments.
Fluent English and strong communication skills.
Proactive attitude, ownership, and a DevOps mindset.

Nice to have:

Experience with Oracle databases.
Experience with dltHub.
Experience with Azure Data Services.
Experience supporting Power BI reporting environments.
Knowledge of data governance, lineage, and metadata management.
Experience building enterprise-level data platforms or data lakes.
Experience in the insurance or financial services industry.
Bachelor’s or Master’s degree in a technical field.

Obowiązki

Design and develop the architecture of a large-scale Central Data Platform.
Build and maintain end-to-end data pipelines covering ingestion, transformation, storage, and consumption.
Integrate data from multiple systems into a consistent data platform.
Design scalable data models aligned with business and analytical requirements.
Develop and optimize ETL and ELT processes using Databricks, Python, PySpark, and dbt.
Prepare reliable datasets for analytics, reporting, and business intelligence.
Ensure data quality, consistency, lineage, security, and performance.
Develop reusable data components and standardize data workflows.
Support automated deployment and infrastructure processes using GitHub and Terraform.
Collaborate with data engineers, architects, analysts, Power BI developers, and business stakeholders.
Translate complex requirements into scalable technical solutions.
Continuously improve the reliability, automation, and maintainability of the platform.

Benefity

Private medical care.
Group insurance.
Multisport card.
English classes are available.
Pinball and PlayStation are available on-site.

Opieka zdrowotna

Ubezpieczenie

Karta sportowa

Kursy językowe

Inne informacje

On-site work in Warsaw (Mokotów) is required at least one day every 2–3 months.

Webellian

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