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Zuletzt aktualisiert: vor 11 Stunden
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Yeah! GlobalBerlin, GermanyDiese Stelle ist in deinem Land nicht verfügbar.
Data Engineer
Axiom Software Solutions LimitedFrankfurt am Main West, HE, DEVor 30+ Tagen
Anstellungsart
- Homeoffice
- Quick Apply
Stellenbeschreibung
Job Role : Data Engineer
Location : Frankfurt Germany (Remote with Occasional travel to Frankfurt)
Job Type : Permanent / Contract
Language : Must be a Fluent German and English speaker
Candidate must be based in Germany
Job 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.