Data Engineer | Python, SQL & dbt | Direct Response Skincare Brand | Full Time

Data Engineer | Python, SQL & dbt | Direct Response Skincare Brand | Full Time Are you a hands-on Data Engineer who can build reliable ingestion pipelines, write production-quality Python and transform complex raw data into trusted, reusable datasets? Are you highly skilled in Python and SQL, with direct experience building dbt models, data warehouses and scalable bronze, silver and gold data layers? Are you the kind of engineer who takes complete ownership, solves problems without waiting to be rescued and ensures business-critical data remains accurate, available and ready for decision-making? We are My Derma Dream, one of the fastest-growing direct-response skincare brands in the United States. Since 2022, we have scaled to nearly nine figures by combining innovative beauty technology, world-class marketing and an uncompromising commitment to execution. Because of our the incredible work of our team, we now generate vast amounts of data across Shopify, Checkout Champ, affiliate networks, advertising platforms, customer systems and other business-critical sources. BUT… Our ability to grow depends on our ability to access, trust and act on our data. We need a highly capable, hands-on Data Engineer who can build and maintain dependable ingestion pipelines, develop scalable dbt models and help create a properly governed data warehouse. You will work closely with our Head of Data & Analytics and future analysts to convert large, slow and complex analytical queries into efficient, reusable data models that power dashboards, reports, attribution analysis and operational decision-making. If you have directly built production data pipelines and warehouses rather than only supporting or observing them… If you are a rock star in both Python and SQL, understand data modelling and have meaningful hands-on experience building dbt models… If you are hardworking, responsive, comfortable working independently and willing to take ownership when critical data pipelines require immediate attention… Then APPLY NOW! =========== Results: - Build and maintain reliable ingestion pipelines that bring data from all key source systems into the bronze layer. - Build scalable dbt models across the bronze, silver and gold layers of the data warehouse. - Turn large, slow and complex queries into efficient, reusable data models for dashboards, reporting and analysis. - Ensure data pipelines, models and production datasets are accurate, monitored, documented and always available. - Give the Head of Data the hands-on engineering support needed to focus on strategic data leadership. =========== Responsibilities: - Write clean, maintainable and well-tested Python and SQL code. - Build and maintain reliable batch, incremental and real-time data ingestion pipelines. - Develop custom Python integrations for systems that are not supported by existing ingestion platforms. - Consume REST APIs, webhooks and third-party SDKs to retrieve business-critical data. - Monitor ingestion jobs, investigate warnings and failures and restore pipelines quickly. - Maintain data freshness, accuracy, completeness and availability. - Build, test and optimise dbt models across bronze, silver and gold data layers. - Work with the Head of Data and analysts to convert business logic into scalable data models. - Deconstruct large analytical queries into dimensions, facts, intermediate models, seed tables and reusable transformations. - Apply Kimball dimensional-modelling principles, including star schemas, fact tables and dimension tables. - Create clear model descriptions, lineage, documentation and data-quality tests. - Troubleshoot merge conflicts, failed deployments and production issues without becoming blocked. - Maintain scheduled dbt jobs across development, staging and production environments. - Optimise BigQuery queries, storage and data-processing costs. - Maintain Git-based version control and CI/CD deployment workflows. - Protect the stability and governance of production gold-layer data. - Support the future development of data lakes, reverse ETL, streaming architecture and event-driven pipelines. - Maintain awareness of API changes, dependency updates and new dbt versions. - Participate in an on-call rota for business-critical data incidents. - Communicate risks, blockers and technical decisions clearly to both technical and non-technical stakeholders. - Use AI-assisted engineering tools responsibly to increase speed, quality and productivity. =========== Requirements: - Willingness to participate in an on-call schedule. - Comfortable operating within a fast-moving, high-performance environment. - Work 6 days per week. - Work 10 hours per day. - Read two books per month. =========== Technical Requirements: - Expert experience in Python & SQL - Experience with Google BigQuery and Google Cloud Platform. - Experience with Fivetran, Hevo or similar managed ingestion platforms. - Experience with Superbase and Elementary are an advantage. - Experience building custom Fivetran connectors or working with connector SDKs. - Experience with Shopify, Checkout Champ, Klaviyo or direct-to-consumer commerce data. - Experience combining ecommerce, attribution, advertising, affiliate and customer data. - Experience building a cloud-based data lake. - Experience with reverse ETL. - Experience with streaming technologies, event-driven systems, webhooks or cloud functions. - Experience with Terraform or other infrastructure-as-code tools. - Experience with Docker or related DevOps tooling. - A GitHub profile, technical portfolio or examples of personal engineering projects. =========== Reward: - Competitive Salary - A clear values, principles & traditions-based culture - Working in an environment of big dreams, speed, aggression, figure-it-out-ability & high leverage. - An opportunity to go all in, every day, all day. If you are looking for the ride of a lifetime, then APPLY NOW!