[HCM] Data Engineer

POSITION OVERVIEW

As a Data Engineer, you will play a pivotal role in architecting and developing modern data warehouse and data lake solutions that serve as the foundation for both batch and real-time analytics, as well as AI-driven systems. You will work closely with cross-functional teams to build a robust, scalable data infrastructure that empowers intelligent applications and enables data-driven decision-making across the organization.

WHAT YOU WILL DO

• Design, build, operate, and continuously evolve modern data architecture to ensure scalability, reliability, and adaptability, supporting business growth and innovation

• Develop, optimize, and fine-tune ETL/ELT pipelines and data processing workflows to integrate data from multiple systems and platforms, ensuring high data quality, performance, scalability, reliability, and cost-efficiency

• Ensure data quality, security, and compliance by implementing best practices, governance policies, and robust security measures to protect sensitive data and meet regulatory requirements

• Manage and optimize database and data warehouse performance, including query optimization, indexing strategies, and performance tuning, to ensure fast, efficient, and reliable data retrieval

• Create and maintain data warehouses and data lakes that support business intelligence and analytics needs across restaurant operations, customer engagement, and supply chain management

• Implement data collection and integration processes from various sources including POS systems, online ordering platforms, inventory management, and customer feedback channels

• Build and maintain comprehensive data documentation including data dictionaries, flow diagrams, and architecture designs

• Mentor and guide the development team on data management best practices, database design, and efficient workflow integration

• Support additional tasks or responsibilities as assigned by the line manager to contribute to the team's and organization's success

Example Projects

- Building a real-time analytics platform to monitor restaurant performance metrics

- Developing customer segmentation data pipelines that power personalized marketing initiatives

- Creating inventory optimization models based on historical sales data and seasonal trends

- Implementing a unified data platform that connects front-of-house and back-of-house operations

1. Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Science, or related field (or equivalent practical experience)

• Minimum 3 years of experience in Data Engineering, Analytics Engineering, or a similar role, with a proven track record in building and maintaining scalable data pipelines and infrastructure

• Proficient in programming with Python and Java/Scala, and experienced in working with CI/CD pipelines

• Strong SQL skills and hands-on experience with the modern data stack on cloud platforms such as GCP, AWS, or Azure

• Practical experience with workflow orchestration tools such as Airflow, Prefect, or Dagster

• Skilled in data modeling and transformation using tools like dbt, Dataform, or equivalent

• Familiar with BI/visualization tools including Superset, Looker, or Metabase

• Solid understanding of distributed data processing and streaming frameworks such as Kafka, Spark, or Flink

• Experience with relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra)

• Strong problem-solving skills, attention to detail, and a self-learning attitude

• Proficient in English, both written and verbal, with the ability to read technical documentation and communicate effectively with cross-functional teams

2. Preferred Skills

• Experience in the hospitality or food service industry

• Knowledge of restaurant technology ecosystems, particularly POS systems integration and customer data platforms

• Experience with containerization and orchestration tools (Docker, Kubernetes)

• Understanding of machine learning pipelines and productionization

• Knowledge of data governance and compliance requirements specific to the food service industry

• Experience building real-time analytics dashboards for operational metrics

• Familiarity with DataOps and DevOps practices