Warehouse and analytics data infrastructure. This role focuses on ingesting operational data from source systems (primarily PostgreSQL), transforming and modeling that data in the data warehouse (currently Snowflake), and preparing reporting-ready datasets and optimized queries for analytics and reporting services. The engineer partners closely with product and software engineering teams to ensure data is reliable, performant, and easy to consume - whether through optimized SQL queries or analytics-friendly data models. This role combines deep technical expertise in data engineering with ownership of data architecture, a version-controlled database codebase, and support for multiple environments. Responsibilities ? Design, develop, and maintain a scalable data warehouse architecture to support analytics and reporting needs. ? Build and manage data ingestion pipelines that move operational data (from PostgreSQL) into the data warehouse (Snowflake) with high reliability and data quality. ? Transform and model raw data into reporting-friendly schemas (e.g., dimensional models, denormalized datasets, or analytics-optimized akeholders to translate business requirements into scalable data solutions. ? Establish and promote data engineering best practices, including naming conventions, documentation, testing, and performance optimization. ? Monitor data pipelines and warehouse performance, proactively identifying and resolving data quality, latency, or scalability issues. ? Contribute to architectural decisions around data modeling, ingestion patterns, and warehouse optimization. ? Participate in agile development processes, additional tasks within the department as assigned by management. Qualifications ? 4–8 years of prof data modeling concepts (e.g., dimensional modeling, star/snowflake schemas, reporting-optimized structures). ? Familiarity with ELT/ETL concepts, data pipelines, and orchestration practices. ? Experience ingesting and transforming data from relational databases, particularly PostgreSQL. ? Solid experience with Git-based version control for database code and data transformations. ? Experience supporting multiple environments (development, staging, production) with controlled deployment processes. ? Strong problem-solving skills and ability
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