• Design, build, and maintain ETL/ELT pipelines from multiple data sources (Shopify, Meta, Google, CRM, etc.) • Own and manage the data warehouse (e.g. BigQuery, Snowflake, Redshift) • Ensure reliable, scalable, and efficient data flow across systems • Monitor and improve pipeline performance, cost, and reliability • Build and maintain data models (dbt or equivalent) • Structure raw data into clean, business-ready datasets (fact/dimension tables) • Define and standardize core business metrics across teams • Enable a consistent single source of truth • Implement validation checks and monitoring to ensure data accuracy • Identify and resolve discrepancies across platforms • Maintain documentation for data definitions and logic • Improve overall trust in data across the organization • Support dashboarding and reporting (Looker, Power BI, etc.) • Partner with marketing, product, and ops teams to deliver clean datasets • Enable faster and more accurate analysis across the business

Paired is a global recruiting agency that pairs remote work with top-tier talent. We help individuals from around the world connect with great companies that are looking for their specific skill set. Our mission is to provide great jobs to talented people, no matter where they are located. About Our Clients Our client is a growing direct-to-consumer e-commerce brand focused on delivering high-quality products and strong customer experiences. As the business scales, they are looking for a Analytics Engineer to build and own our data foundation end-to-end. This role is responsible for designing data pipelines, managing the data warehouse, and creating reliable, structured datasets that power decision-making across marketing, product, and operations. This is not a reporting-only role. The focus is on building scalable data systems that ensure accuracy, consistency, and a single source of truth across the business. Responsibilities - Design, build, and maintain ETL/ELT pipelines from multiple data sources (Shopify, Meta, Google, CRM, etc.) - Own and manage the data warehouse (e.g. BigQuery, Snowflake, Redshift) - Ensure reliable, scalable, and efficient data flow across systems - Monitor and improve pipeline performance, cost, and reliability - Build and maintain data models (dbt or equivalent) - Structure raw data into clean, business-ready datasets (fact/dimension tables) - Define and standardize core business metrics across teams - Enable a consistent single source of truth - Implement validation checks and monitoring to ensure data accuracy - Identify and resolve discrepancies across platforms - Maintain documentation for data definitions and logic - Improve overall trust in data across the organization - Support dashboarding and reporting (Looker, Power BI, etc.) - Partner with marketing, product, and ops teams to deliver clean datasets - Enable faster and more accurate analysis across the business

Role Description We’re hiring our first dedicated analytics engineer to join an established data engineering team. You won’t be building alone — you’ll work alongside data engineers who own the pipelines and infrastructure (Fivetran, Databricks), and your job is to build the analytics layer on top: reliable data models within our medallion architecture (bronze, silver, gold), clean dashboards, and governed metrics that teams across the company can trust and self-serve. This is a hands-on individual contributor role, but collaboration is central to the work. You’ll spend your time writing SQL, building and maintaining gold-layer models in Databricks, and creating dashboards in Omni Analytics — but you’ll also be a regular presence in conversations with Product, CS, Sales, and Marketing, translating their questions into reliable analytics and surfacing insights they wouldn’t find on their own. Strong cross-team communication skills matter as much as technical depth here. What You’ll Do: - Data Modeling & Transformation - Build and maintain dimensional and semantic models in Databricks that serve as the analytics layer for the company, working within a medallion architecture (bronze, silver, gold). - Own the gold layer — write clean, tested, version-controlled SQL transformations that turn curated silver-layer data into business-ready tables optimized for reporting and analysis. - Partner with data engineers on data quality, lineage, and freshness across the medallion layers to ensure models are reliable and well-documented. - Dashboards & Business Intelligence - Design and build dashboards and topics in Omni Analytics for Product, Client Success, Sales, Marketing, and executive stakeholders. - Implement governance practices for dashboards: naming conventions, documentation, version control, and testing. - Create client-facing analytics views that can be shared externally to demonstrate platform value. - Metrics & Governance - Collaborate with Product and leadership to document KPI definitions and implement them consistently across all reporting surfaces. - Contribute to a metric catalog so that stakeholders reference the same numbers from the same source. - Flag data quality issues proactively and work with the data engineering team to resolve them. - Investigations & Analysis - Conduct deep-dive investigations into conversion drops, data mismatches, and funnel issues using SQL and platform tooling. - Document findings and build repeatable analysis runbooks so investigations don’t start from scratch each time. - Partner with product engineering to identify gaps in event instrumentation and recommend improvements. - Stakeholder Enablement - Help internal teams learn Omni Analytics so they can answer routine questions without filing a request. - Write lightweight documentation for dashboards, data models, and common queries. Qualifications - 5+ years in analytics engineering, BI development, or product analytics roles. - Advanced SQL — you write complex, performant queries daily and are comfortable with window functions, CTEs, and large-scale data. - Hands-on experience with a modern BI tool (Omni, Looker, or similar) — building explores, semantic layers, and governed dashboards. - Experience with Databricks, BigQuery, or a comparable cloud analytics platform for data modeling and transformation. - Familiarity with medallion layer architecture (bronze/silver/gold) is strongly preferred. - Familiarity with ELT/ETL orchestration tools (Fivetran, dbt, or similar). Requirements - Product-minded: you don’t just build tables — you understand what questions the business is trying to answer and work backward from there. - Builder mentality: you prefer creating tested, documented, reusable assets over one-off queries. - Clear communicator: you can explain data findings to non-technical stakeholders in writing and in conversation. You’re comfortable presenting to CS, Sales, Marketing, and Product teams and translating between technical and business language. - Cross-team collaborator: you proactively build relationships across departments, seek out context before building, and make sure your work is shaped by the people who will use it — not just the people who requested it. - Comfortable with ambiguity: this is a first-of-its-kind role at Opiniion, and you’ll help shape how analytics work gets done. Nice-to-Haves - dbt or similar modeling/testing frameworks. - Python for light ETL, scripting, or anomaly detection. - Comfortable working with data from MongoDB or other NoSQL sources. - GA4 or product analytics instrumentation experience. - Proptech, real estate technology, or multifamily industry experience. - Experimentation platforms or statistical analysis background. What Success Looks Like - In your first 90 days, you’ll have shipped your first governed dashboards in Omni and earned trust with at least one stakeholder team. - Within 6 months, here’s what we’d expect: - Core business KPIs are modeled in Databricks and surfaced through Omni dashboards that stakeholders actively use. - The majority of routine analytics questions from Product, CS, Sales, and Marketing are answered through self-service dashboards rather than ad-hoc requests. - Data models are documented, tested, and version-controlled — not tribal knowledge. - You’ve conducted at least one meaningful investigation that identified a root cause of a platform or funnel issue and informed a product fix. - Executive dashboards are in production and shared with leadership and clients. Benefits - Comprehensive healthcare plans, encompassing medical, dental, and vision insurance, along with group life coverage. Opiniion covers 40-90% of the premium cost for employees and all dependents. - 401(k) retirement plan with a 100% corporate match on the first 1% and 50% match on the next 5%. - Pre-tax Health Spending Accounts (HSA). - Paid Parental Leave for all new parents (including adoption or foster care). - Unlimited Time Off policies. - 10 Paid Holidays annually. - Monthly Gym Reimbursement benefit.

• Develop and maintain Kin’s Looker semantic layer, including LookML views, explores, and user-friendly dashboards • Partner with domain data engineers to standardize definitions, metrics, and calculations while performing data analysis, validation, and exception reporting across business lines • Support and administer Looker or similar BI platform (permissions, performance tuning, content lifecycle, QA) • Model and maintain dimensional models to support enterprise analytics and reporting • Collaborate with Finance, Marketing, and Product to deliver and maintain high-impact reports and KPIs • Implement data quality monitoring for trusted business reporting • Champion documentation and reusable data patterns for BI development • Partner with the broader data platform team to evolve our Lakehouse and data governance practices