Data Engineer
Job Role: Data EngineerLocation: Frankfurt Germany (Remote with Occasional travel to Frankfurt)Job Type: Permanent/ContractLanguage : Must be a Fluent German and English speakerCandidate must be based in GermanyJob Description:4-6 years of experience in various data architecture and engineering roles within data & analytics
Collaborate with stakeholders to understand and document data requirements, business rules, and objectives for the data platform.
Design and develop conceptual, logical, and physical data models that accurately represent the organization's data assets and support its business needs.
Ensure designs meet documented objectives for reliability, scalability, supportability, user experience, security, governance, performance and more
Implement data engineering practices, including normalization, denormalization, and indexing, to ensure data integrity, performance, and scalability.
Work closely with architects to integrate data engineering into the overall platform architecture, ensuring efficient data processing and storage.
Communicate effectively with technical and non-technical stakeholders to present and explain data engineering, design decisions, and recommendations.
3+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
Knowledge of Sagemaker/Jupyter, and data lake
Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required.
Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC
Ensuring that data are modelled and processed according to architecture and requirements both functional and non-functional
Understanding and implementing required development guidelines, design standards and best practices
Delivering right solution architecture, automation and technology choices
Working cross-functionally with enterprise architects, information security teams, and platform teams
Suggesting and implementing architecture improvements.
Originally posted on Himalayas
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Collaborate with stakeholders to understand and document data requirements, business rules, and objectives for the data platform.
Design and develop conceptual, logical, and physical data models that accurately represent the organization's data assets and support its business needs.
Ensure designs meet documented objectives for reliability, scalability, supportability, user experience, security, governance, performance and more
Implement data engineering practices, including normalization, denormalization, and indexing, to ensure data integrity, performance, and scalability.
Work closely with architects to integrate data engineering into the overall platform architecture, ensuring efficient data processing and storage.
Communicate effectively with technical and non-technical stakeholders to present and explain data engineering, design decisions, and recommendations.
3+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
Knowledge of Sagemaker/Jupyter, and data lake
Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required.
Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC
Ensuring that data are modelled and processed according to architecture and requirements both functional and non-functional
Understanding and implementing required development guidelines, design standards and best practices
Delivering right solution architecture, automation and technology choices
Working cross-functionally with enterprise architects, information security teams, and platform teams
Suggesting and implementing architecture improvements.
Originally posted on Himalayas
Apply Now