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<p><strong>About the Role </strong></p><p>This role is for an <strong>Analytics Engineer</strong> who can build production systems, work across the stack when needed, and help the business make better decisions through reliable data infrastructure and analysis. You will focus on backend systems, integrations, data pipelines, reporting workflows, and internal tools that connect ecommerce operations, marketing, customer behavior, inventory, fulfillment, and finance. You should be comfortable working with incomplete information, making sense of messy data, and turning business questions into dependable technical systems.</p><p><br></p><p>This is not a pure analytics role and not a pure backend role. It sits at the intersection of backend engineering, data engineering, analytics, and e-commerce operations. The right person will be able to build APIs, automate workflows, analyze datasets, create or maintain pipelines, and communicate insights to non-technical stakeholders.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li><strong>Backend systems</strong>: Build and maintain backend services, APIs, integrations, webhooks, jobs, and internal tools that support e-commerce operations.</li><li><strong>Data engineering</strong>: Design and maintain data pipelines that move data between Shopify, marketing platforms, analytics tools, databases, spreadsheets, warehouses, and internal systems.</li><li><strong>Data analysis</strong>: Analyze customer, order, product, inventory, fulfillment, marketing, and operational data to identify trends, diagnose issues, and support business decisions.</li><li><strong>E-commerce integrations</strong>: Work with Shopify APIs and third-party e-commerce tools to connect systems and automate workflows.</li><li><strong>Reporting and dashboards</strong>: Create reliable reporting foundations for business teams, including dashboards, data models, recurring reports, and self-serve analysis workflows.</li><li><strong>Full-stack contribution</strong>: Support frontend or internal tool development when needed, especially where data visibility or operational workflows require user interfaces.</li><li><strong>Technical ownership</strong>: Improve reliability, observability, data quality, documentation, and maintainability across backend and data systems.</li></ul><p><br></p><p><strong>What You’ll Work On:</strong></p><p>You may work on projects such as building a pipeline from Shopify into a data warehouse, automating recurring reports, improving order and customer data models, integrating marketing and attribution data, building internal dashboards, connecting fulfillment or inventory systems, and creating backend services that make operations more scalable.</p><p>You will also help answer business questions with data. For example, you may investigate changes in product performance, customer retention, marketing efficiency, inventory availability, returns, fulfillment delays, or customer lifetime value. The goal is not only to produce analysis, but to build systems that make good analysis repeatable and trustworthy.</p><p><br></p><p><strong>Requirements</strong> :</p><ul><li><strong>Experience level</strong>: Mid-to-senior engineer (3-5 years) with experience building production backend systems and working with real business data.</li><li><strong>Shopify API experience</strong>: Valuable for extracting, transforming, and operationalizing e-commerce data.</li><li><strong>Backend engineering: </strong>Strong ability to design and implement APIs, services, database schemas, integrations, background jobs, and automation workflows.</li><li><strong>Data skills: </strong>Strong SQL and practical experience with data modeling, ETL or ELT workflows, data quality, and analytical problem solving.</li><li><strong>E-commerce context</strong>: Experience with Shopify, e-commerce platforms, order/customer/product data, marketing data, or operational systems is preferred.</li><li><strong>Full-stack flexibility</strong>: Ability to contribute to frontend or internal tools using technologies such as React, Vue.js, JavaScript, or TypeScript when needed.</li><li><strong>Business orientation</strong>: Ability to translate business questions into technical requirements, analysis plans, and scalable systems.</li><li><strong>Communication</strong>: Ability to explain technical and analytical findings clearly to both technical and non-technical stakeholders.</li><li><strong>Startup adaptability</strong>: Comfort operating with ambiguity, learning unfamiliar systems, and prioritizing work based on business impact.</li></ul><p><br></p><p><strong>Nice to have: </strong></p><ul><li><strong>Data warehouse experience</strong>: Helpful for building reliable analytics infrastructure using tools such as BigQuery, Snowflake, Redshift, Postgres, or similar systems.</li><li><strong>Python experience</strong>: Useful for scripting, automation, data pipelines, analysis, and backend services.</li><li><strong>Marketing analytics experience</strong>: Helpful for connecting e-commerce performance to paid media, email, attribution, cohort behavior, and retention analysis.</li><li><strong>Business intelligence tools</strong>: Useful for creating dashboards and reporting workflows in tools such as Looker, Tableau, Metabase, Mode, or similar platforms.</li><li><strong>Cloud infrastructure experience</strong>: Helpful for owning production workflows, scheduled jobs, storage, monitoring, and deployment.</li><li><strong>Data governance and quality experience</strong>: Valuable for ensuring that teams can trust the metrics and reports they use.</li></ul>
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