Data Engineer
Summary
Data Engineer who manages and builds data pipelines and ETL/ELT processes into the company's Big Data platform (Google Cloud experience a plus), maintains the data warehouse, and ensures data quality for BI, analysts, and AI initiatives. Needs SQL, Python or Java, and 1-2 years of data engineering experience.
Job Descriptions :
- Manage, monitor, and maintain existing data pipelines to ensure reliable and efficient data processing, while developing new pipelines as business needs evolve.
- Extract and integrate data from multiple sources into the company’s Big Data platform.
- Develop and maintain ETL/ELT processes to ensure data is accurate, consistent, and ready for use.
- Collaborate with cross-functional teams to understand data requirements and deliver effective data solutions.
- Support the development and continuous improvement of the company’s data warehouse and data platform.
- Monitor data platform performance, identify potential issues or anomalies, and perform optimization when needed.
- Maintain and promote data quality standards across BI teams, Data Analysts, Data Scientists, and other data stakeholders.
- Create and maintain data dictionaries, technical documentation, and other data-related references.
- Support AI-driven initiatives by preparing and integrating reliable data sources and data pipelines required for AI-based solutions.
Requirements :
- Bachelor’s degree in Information Technology, Information Systems, Computer Science, or a related field.
- 1–2 years of hands-on experience in Data Engineering or a related data role.
- Strong proficiency in SQL and at least one programming or scripting language, preferably Python or Java.
- Good understanding of databases, data warehouse concepts, and ETL/ELT processes.
- Familiar with building, maintaining, and monitoring data pipelines in a cloud environment; experience with Google Cloud Platform (GCP) is a strong advantage.
- Good understanding of data quality principles and their practical application in data processes.
- Basic understanding of AI/ML concepts and an interest in supporting AI-driven data solutions.
- Strong analytical thinking and problem-solving skills.
- Able to communicate and collaborate effectively with both technical and non-technical stakeholders.
- Detail-oriented, curious, proactive, and eager to learn and grow in data engineering and emerging technologies.
- Experience integrating data pipelines with customer engagement or marketing platforms, such as Braze or similar tools, including API-based data integration, is a plus.