Senior Data Engineer

About the Company

Kenko is building a future where healthcare is transparent, accessible, and tailored to individual needs.

About the Role

We are seeking a talented and experienced Senior Data Engineer to join our growing team. You will be instrumental in designing, building, and maintaining our data infrastructure, ensuring the reliability, efficiency, and scalability of our data pipelines and data warehouse. This is a critical role that will enable data-driven decision-making across the company, supporting product development, analytics, and operational insights.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from various sources into our data warehouse.
• Build and optimize data models for performance and ease of use by data analysts and scientists.
• Collaborate with product teams, data analysts, and other engineers to understand data requirements and deliver robust data solutions.
• Implement data quality checks and monitoring processes to ensure data accuracy and reliability.
• Manage and improve our cloud-based data infrastructure (likely on AWS).
• Troubleshoot and resolve data-related issues, ensuring high availability of data.
• Develop and maintain documentation for data pipelines, data models, and infrastructure.
• Mentor junior team members and contribute to data engineering best practices.

Qualifications

• Proven experience as a Data Engineer, with a focus on building and managing data pipelines and data warehouses.
• Strong proficiency in SQL and data modeling techniques.
• Extensive experience with programming languages commonly used in data engineering, such as Python.
• Hands-on experience with cloud platforms, particularly AWS, including services like S3, Redshift, EMR, Glue, or similar.
• Experience with data orchestration tools (e.g., Airflow) is a plus.
• Familiarity with containerization technologies like Docker and orchestration like Kubernetes is beneficial.
• Understanding of data warehousing concepts and best practices.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Required Skills

• Proven experience as a Data Engineer.
• Strong proficiency in SQL.
• Experience with Python.
• Hands-on experience with AWS.
• Experience with data orchestration tools.
• Familiarity with Docker and Kubernetes.
• Understanding of data warehousing concepts.
• Excellent problem-solving skills.
• Strong communication skills.

Preferred Skills

• Experience with data orchestration tools (e.g., Airflow).
• Familiarity with containerization technologies like Docker.
• Experience with orchestration like Kubernetes.