Senior Data Engineer - Data Modeler

March 11

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RemoteStar

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RemoteStar is a global recruitment service that specializes in hiring top-quality tech talent. By assembling diverse teams with vetted developers from various regions, RemoteStar ensures high-quality staffing while maximizing cost efficiency for companies. The service includes a rigorous vetting process, technical matching, and full onboarding support, allowing businesses to focus on their core operations while RemoteStar handles the administrative aspects of recruitment and team management.

Remote Team Hiring • Product Development • Software Development • Computer Software • Remote Working

11 - 50 employees

Founded 2020

🤝 B2B

🎯 Recruitment

☁️ SaaS

📋 Description

• The broad scope of responsibility of this role requires a solid experience and understanding of data models, data analysis, data management, and programming languages to develop, analyse, and maintain data models. • This role involves working closely with data architects, business analysts, and data consumers to ensure that data models meet business requirements and are aligned with industry best practices. • Create and implement logical and physical data models that support structured and unstructured data across RDBMS and big data platforms. • Design and implement semantic data models that optimise data accessibility, performance, and usability for Business Intelligence (BI) and analytics. • Create and maintain documentation of data models, including entity-relationship diagrams (ERDs), data flow diagrams (DFDs), and data dictionaries to ensure clarity and alignment across teams. • Develop and maintain metadata repositories and data lineage documentation to track data transformations and dependencies. • Work closely with business analysts, data engineers, and data consumers to gather requirements and translate business needs into data models. • Own the Model governance for any changes to the model from users. • Partner with data architects to ensure data models conform to the data strategy and best practices in data management and integration. • Work with Architecture teams to expand the existing models. • Conduct regular data model reviews to incorporate changes in data platforms, evolving business requirements, and performance optimisations. • Ensure all data models comply with data quality, security, and governance standards. • Analyse data lineage from source systems to the final semantic layer, identifying transformation rules and their impact on the physical data model. • Create data models that support migrations, conversions, and transformations as data platforms evolve and new standards are defined.

🎯 Requirements

• 7 -10 years of experience as a Data Modeler or in a similar role, with expertise in data modelling principles (conceptual, logical, and physical). • 5+ years of hands-on experience in data modelling, databases, and data analysis. • Strong understanding of data modelling concepts, including normalization, denormalization, dimensional modelling, and Data Vault 2.0 methodology (certification or hands-on experience preferred). • Proficiency in data modelling tools such as ER/Studio, ERwin, SQLDBMS, or Sparx Systems. • Hands-on experience with relational databases (RDBMS) such as PostgreSQL, Oracle, SQL Server, MySQL and data warehousing solutions. • Knowledge of data integration, ETL/ELT workflows, and data migration. • Experience in Semantic Data Modelling, including Business Intelligence layer data modelling and familiarity with data visualization tools. • Strong understanding of database management systems (DBMS), SQL, and query optimisation. • Familiarity with programming languages like SQL, Python, and a strong understanding of data warehousing and ETL techniques. • Experience in metadata management, data privacy standards, and compliance. • Expert knowledge of cloud-based data platforms (AWS, Azure, or GCP) and data Lakehouse architectures (Medallion architecture, Delta Lake, Snowflake, or Databricks).