Data Architect

160 - 180 PLN/ godz./ godz.B2BB2B (netto)

SeniorZdalnie·WarszawaFull-time·B2B

#474785·Dodano wczoraj·0

Źródło: justjoin.it

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Tech Stack / Keywords

Data modelingSQL Databricksdata governanceLakehouse Architecture

Podsumowanie oferty

Design, develop, and maintain domain data models, translating business requirements into scalable data solutions. Take ownership of the domain data foundation and work with SQL and Databricks across data products.

Wymagania

Requirements:

Excellent communication, stakeholder management, and decision-making skills.
Solid experience in data modelling, particularly conceptual and logical data modelling.
Strong SQL knowledge and hands-on experience with modern data platforms, preferably Databricks.
Ability to understand business needs and transform them into technical specifications and scalable data models.
Good understanding of lakehouse architecture, data integration, and analytical data environments.
Experience working with cross-functional teams, including business stakeholders, Product Managers, Data Engineers, and Technical Leads.

Nice to have:

Practical experience with Databricks, Delta Lake, and cloud-based data platforms.
Knowledge of data governance, data quality management, metadata, and data lineage.
Familiarity with Agile methodologies and DevOps practices.
Understanding of analytics, reporting solutions, and data product development.

Obowiązki

Key Responsibilities:

Design, develop, and maintain domain data models, translating business requirements into scalable, reusable, and well-structured data solutions.
Provide technical direction and support to engineering teams, ensuring data solutions comply with established standards and business expectations.
Oversee modifications to domain data assets, maintaining their integrity, consistency, and reliability.
Take ownership of the domain data foundation, ensuring accurate data definitions, high data quality, and consistency across data products.
Collaborate with business stakeholders, Product Managers, Analytical Product Managers, and delivery teams to identify priorities and coordinate data-related initiatives.
Oversee data operations and service performance, identifying opportunities to improve efficiency and optimize processes.
Promote and support the implementation of data governance standards, metadata management, data lineage, and data quality practices.

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