Data Engineer

Job Responsibility: 

• Build and manage the data foundation that makes AI accessible and scalable across the organization.
• Enable seamless integration of enterprise data through APIs middleware and data pipelines.
• Deliver trusted high-quality and AI-ready data assets for analytics automation and AI solutions.
• Create scalable data products semantic models and integration frameworks that simplify data consumption.
• Connect business applications platforms and external services to provide unified and accessible enterprise data. 
• Design develop and maintain enterprise data integrations and API-based data exchange.
• Build and operate scalable data pipelines that provide reliable access to business-critical data.
• Integrate ERP CRM HR Finance Manufacturing and external systems into the enterprise data platform.
• Manage and optimize data ingestion transformation and delivery processes.
• Develop and maintain semantic models that make data understandable and consumable for AI and business users.
• Ensure data quality lineage consistency and governance across integrated systems.
• Create reusable integration patterns data products and data services.
• Monitor troubleshoot and continuously improve integration and pipeline performance.
• Support reporting analytics automation and AI initiatives with trusted and accessible datasets.
• Collaborate with business stakeholders to identify and prioritize data integration opportunities.
• Contribute to the evolution of the enterprise data architecture and AI data platform roadmap.
• Maintain technical documentation standards and best practices for integrations and data assets.

Qualifications :

Job Requirements:

• Bachelors degree with majored in computer or data science or similar field. 
• > 3 years experience in data engineering / science. 
• Strong experience in Data Engineering and Enterprise Data Integration.
• Expertise in API development and integration (REST OData).
• Experience with Boomi or similar Integration Platform-as-a-Service (iPaaS) solutions.
• Advanced SQL and data transformation skills.
• Experience designing and operating ETL/ELT pipelines.
• Knowledge of Snowflake or similar database and/or data lake solutions.
• Understanding of data lake data warehouse and modern data platform architectures.
• Experience with semantic data modeling and business data abstraction layers.
• Knowledge of JSON XML Parquet and further common data formats.
• Experience with source control CI/CD and DevOps practices.
• Understanding of data governance security privacy and compliance principles.
• Experience supporting AI and machine learning use cases through data engineering.
• Familiarity with event-driven architectures messaging and real-time data integration.
• Passion for making data accessible understandable and usable for AI and business value creation.
• Strong analytical and systems-thinking capabilities.
• Ability to translate complex business requirements into scalable data solutions.
• Strong stakeholder engagement and communication skills.
• Collaborative mindset with the ability to work across business and technology functions.
• Ownership mentality with accountability for end-to-end data solutions.
• Strong problem-solving and troubleshooting capabilities.
• Curiosity for emerging AI data and integration technologies.

Remote Work :

No

Employment Type :

Full-time