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Data Engineer – Data & AI (m/w/x)
Developing dynamic ELT pipelines with Snowflake, Azure Data Factory, DBT, and Dagster for enterprise data insights. Three years of analytics tool experience, SQL, and Python required. Support for idea realization, diversity, and development.
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Anforderungen
- University degree in IT or business administration
- Focus on computer science, data science, or data engineering
- At least three years of experience with analytics tools
- Experience with SQL and Python
- Architectural understanding of databases and ETL/ELT pipelines
- Knowledge of SAP (BW, HANA, SAC)
- Knowledge of analytics front-end tools
- Demonstrated enterprise mindset
- Ability to align data-engineering solutions with business strategy
- Alignment with architecture, governance, security, compliance, and operational requirements
- Experience using AI coding assistants
- Experience using AI-enabled data-platform tools
- Familiarity with data science platforms on hyperscalers
- Familiarity with data lake platforms on hyperscalers
- Enthusiasm for engineering tasks
- Enthusiasm for implementation of business requirements
Aufgaben
- Collaborate with data scientists, business analysts, and architects to shape data solutions
- Drive implementation, testing, and support of modern data pipelines
- Develop efficient approaches to data ingestion, preparation, integration, and operationalization
- Contribute to strong data governance and compliance standards
- Develop dynamic ELT pipelines using Snowflake, Azure Data Factory, DBT, and Dagster
- Create scalable, secure, reusable, and maintainable data solutions
- Ensure alignment with enterprise architecture standards and best practices
- Apply AI in ways that support business objectives
- Ensure adherence to security, privacy, governance, and responsible AI principles
- Design and productionize data foundations for AI-powered analytics
- Ensure AI systems have access to high-quality data, features, embeddings, metadata, and evaluation datasets
- Establish and enhance governance frameworks and processes with Data Science teams, Data Cloud Architects, and business stakeholders
- Build strong relationships across IT, Data, Sales, Operations, Marketing, Finance, and other business functions
- Foster alignment and collaboration across the organization
- Help maximize data availability, reliability, and accuracy with DevOps, MLOps, and Analytics Engineers
- Continuously improve data quality to enable innovative data products
- Gain a deep understanding of business requirements and use cases
- Translate insights into effective data-driven solutions
- Drive continuous process improvement initiatives to enhance efficiency and service delivery
- Create clear documentation and engaging presentations for knowledge sharing and communication
Berufserfahrung
Ausbildung
Sprachen
Tools & Technologien
Benefits
- Attractive compensation package
- Market-oriented salaries
- Diversity support
- Opportunity seizing support
- Potential development support
- Idea realization support
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