Design, build, and maintain robust data pipelines and warehouses that support analytics, machine learning, and real-time data products. Integrate and curate complex datasets from multiple sources, ensuring data quality, accessibility, and scalability. Contribute to evolving the data infrastructure, implement best practices across the software development lifecycle, and help deliver actionable insights in a dynamic, innovative environment.
Requirements
- Minimum of 2 years of experience designing, building, and maintaining data pipelines or warehouses.
- Strong proficiency in SQL for analytics, reporting, and building ETL transforms; Python or similar programming experience preferred.
- Experience designing datasets that integrate multiple sources and meet analytical or operational needs.
- Familiarity with modern cloud-based data stacks (e.g., BigQuery, dbt, Apache Airflow, or equivalent).
- Prior experience in supporting analytics, machine learning, or product data initiatives is a plus.
Responsibilities
- Design, architect, and maintain core datasets, data marts, and feature stores for analytics and machine learning.
- Build and optimize ETL pipelines integrating data from internal databases, clickstream sources, and external APIs.
- Collaborate with engineers, analysts, data scientists, and product teams to understand data needs and provide high-quality solutions.
- Ensure data quality, consistency, and reliability across datasets and pipelines.
- Implement best practices for data engineering across the software development lifecycle.
- Contribute to the development of real-time data products using technologies such as Apache Kafka.
Other
- Collaborate with engineers, analysts, data scientists, and product teams to understand data needs and provide high-quality solutions.
- Excellent collaboration skills and ability to work with cross-functional teams to understand requirements and deliver high-quality solutions.
- Strong ownership, attention to detail, and ability to manage projects from ideation through deployment and maintenance.
- Flexible remote work opportunities.
- Work in a collaborative, innovative environment with cutting-edge data technologies.
