Data Engineers

Accountabilities: Design, build, and maintain BigQuery datamarts and analytical tables for BI reporting and analytics. Develop scalable data models using star schema, snowflake, dimensional, and denormalized approaches. Optimize query performance, storage efficiency, and data warehouse workloads. Build and maintain data pipelines for ingestion, transformation, and loading into analytics environments. Develop transformation workflows using SQL, dbt, or similar data transformation frameworks. Implement data validation and quality controls to maintain accuracy and consistency across datasets. Establish and maintain data standards, naming conventions, schema management, documentation, and version control. Monitor data pipelines, troubleshoot failures, and resolve data inconsistencies. Collaborate with BI teams to ensure datasets meet semantic-layer and dashboard requirements. Deliver optimized, analytics-ready datasets that minimize complex transformations within BI tools. Contribute to continuous improvements in data architecture, engineering processes, and analytics workflows. Requirements: 3+ years of experience in Data Engineering, Analytics Engineering, or a closely related field. Strong SQL expertise, particularly for analytical workloads and complex data transformations. Hands-on experience with cloud data warehouses such as BigQuery, Amazon Redshift, Snowflake, or similar platforms. Proven experience designing dimensional, star-schema, or other scalable data models. Experience building and maintaining analytics-ready datamarts. Strong understanding of data warehousing, data pipelines, data modeling, and BI/analytics requirements. Experience with dbt or similar data-transformation frameworks is preferred. Familiarity with Git-based development workflows and CI/CD for data pipelines is an advantage. Experience working with BI platforms such as Looker, Tableau, or Power BI is a plus. Familiarity with retail or multi-location data environments is beneficial. Strong analytical, problem-solving, documentation, and collaboration skills. Knowledge of prompt engineering and AI-assisted workflows is an advantage. Benefits: Fully remote work environment. Full-time position. Compensation of up to $17 per hour. Opportunity to work with modern cloud data warehousing and analytics technologies. Hands-on experience with BigQuery, data modeling, datamarts, and scalable data pipelines. Collaboration with BI and analytics teams on business-critical datasets. Exposure to modern data engineering practices, including dbt, Git, CI/CD, and AI-assisted workflows.