Senior Analytics Engineer

At Ryz Labs, we’re looking for a hands-on Senior Data Engineer / Analytics Engineer to own and evolve one of our clients’ data platforms, reporting layer, and AI-driven data capabilities. You’ll report directly to the Head of Data & Analytics and operate as a high-impact individual contributor across finance, operations, merchandising, marketing, and product. This is a builder role, not a people manager role. You’ll be expected to move quickly, work scrappily, and take ownership from problem definition through implementation. This role is ideal for someone who thrives in a startup or scale-up environment, where speed, iteration, and pragmatism matter more than perfection. What You’ll Do • Own and evolve data architecture across ingestion, transformation, and reporting layers, with a centralized cloud data warehouse. • Build and maintain scalable data pipelines across a variety of internal and external data sources, ensuring reliability, completeness, and accuracy. • Develop robust validation frameworks to monitor data quality and quickly identify issues. • Write and optimize complex SQL to power analytics, reporting, and business decision-making. • Design and maintain data models that support financial reporting, operational analytics, and merchandising insights. • Partner closely with Finance to ensure accurate, reconcilable reporting across revenue, costs, and unit economics. • Build and maintain dashboards and reporting used by leadership to drive decisions across the company. • Identify and resolve data issues quickly, balancing speed and accuracy in a fast-moving environment. • Support integrations between core business systems and ensure clean, consistent data across platforms. • Explore and implement AI-driven workflows that enhance data accessibility and decision-making. • Automate manual reporting processes and improve operational efficiency across teams. • Act as a cross-functional partner, translating ambiguous business questions into clear, actionable insights. What We’re Looking For • 5–10+ years of experience in data engineering, analytics engineering, or advanced analytics roles. • Strong experience with GCP and BigQuery, including materialized views, scheduled queries, and large-scale SQL optimization. • Experience with modern data ingestion tools—Airbyte (Cloud or OSS) strongly preferred; comfort managing connectors, debugging sync failures, and building validation frameworks. • Strong proficiency in SQL and data modeling, with comfort using AI tools (e.g., Claude Code) to accelerate development. You should be fluent in CTEs, window functions, UNION ALL patterns, date-spine techniques, and anti-join logic. • Proven experience supporting financial reporting and working closely with finance teams—P&L reconciliation, COGS analysis, revenue waterfalls, and unit-economics datasets. • Experience building dashboards and reporting in modern BI tools. • Familiarity with AI workflows and building structured datasets for LLM-powered agents. • Experience working across multiple business domains (ops, marketing, finance, product, etc.). • Strong ownership mindset with the ability to operate independently. • Comfortable in a fast-paced, ambiguous environment with shifting priorities. Bonus Points • Experience with ERP or inventory management systems (especially warehouse/3PL integrations). • Experience in ecommerce, recommerce, logistics, or marketplace businesses—especially Shopify-based platforms. • Familiarity with multi-touch attribution, post-purchase surveys (e.g., Fairing/PPS), or event-level GA4 data. • Experience with customer cohort analysis, retention modeling, or LTV forecasting. • Exposure to pricing, inventory aging, or supply chain/fulfillment data systems. • Experience with Klaviyo, Attentive, or similar lifecycle marketing data integrations. • Familiarity with demographic enrichment tools or custom API connector development.