• Shape large-scale data architecture vision and roadmap • Establish governance, security frameworks, and regulatory compliance standards • Lead strategy around platform selection, integration, and scaling • Guide organizations in adopting data lakehouse • Lead technical discovery sessions • Translate complex architectures into clear, actionable value • Align architecture recommendations with business growth and goals • Design and implement modern data lakehouse architectures • Build and manage ETL/ELT pipelines at scale • Implement data quality monitoring, lineage tracking, and schema versioning • Develop cost-optimized, scalable, and compliant data solutions • Define and track success metrics

🚀 Join the Future of Commerce with Whatnot! Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. 💻 Role At Whatnot data engineers build foundational data systems that power product development, experimentation, machine learning, and operational decision-making across the company. As an Data Engineer on the Notifications Platform, you will play a critical role in owning and evolving one of the highest-volume and highest-impact data domains at Whatnot. Notifications generate hundreds of millions of events per day, and the underlying data systems support everything from ML iteration and experimentation to adhoc engineering debugging. In this role, you will define the technical direction for the Notifications data mart, harden it to production-grade reliability, and set new patterns for domain-owned data engineering. Working in a highly cross-functional role, you will collaborate closely with Product Engineers, Data Scientists, ML Engineers, and the Analytics Platform team. You’ll make key architectural decisions around data modeling, reliability, latency, and cost — and then make them real. On any given day, you will: - Own data architecture end-to-end. Define how we capture, model, and serve critical business data—then implement it in production. You’ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency. - Build mission-critical pipelines. Develop and operate batch data workflows that process high-volume events related to notifications with tight guarantees for latency, completeness, and accuracy. - Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and production applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams. - Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable. - Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems. - Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, self-healing, maintainable data assets. We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs. 👋 You Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here. As our next Data Engineer, you bring deep experience designing reliable, scalable data systems and are excited to take true ownership of a complex product domain. You should have 5+ years of experience in the data or software engineering domain, plus: - Strong experience building and maintaining production-grade data pipelines with clear SLAs, monitoring, and alerting - Deep expertise in SQL, including complex model graphs, dependency management, and performance optimization - Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows. - Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations). - Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning. - Proven track record working with large-scale datasets (hundreds of millions of rows per day) - Experience designing data models that balance analytics, ML, and operational debugging use cases - Strong systems thinking — you consider correctness, latency, cost, and maintainability together - Self-starter ethic, thriving under a high level of autonomy - Exceptional interpersonal and communication skills in cross-functional environments 💰Compensation For Full-Time (Salary) US based applicants: $195,000/year to $230,000/year + benefits + equity. The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity. 🎁 Benefits - Generous Holiday and Time off Policy - Health Insurance options including Medical, Dental, Vision - Work From Home Support - Home office setup allowance - Monthly allowance for cell phone and internet - Care benefits - Monthly allowance for wellness - Annual allowance towards Childcare - Lifetime benefit for family planning, such as adoption or fertility expenses - Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally - Monthly allowance to dogfood the app - All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). - Parental Leave - 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence. 💛 EOE Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

• Lead the architecture and development of complex data integration solutions using Microsoft Fabric • Design bidirectional data flows between Fabric and manufacturing systems (Infor M3, Salesforce, Anaplan, OPLIT) • Build advanced ETL pipelines that can handle diverse business data patterns, with preference for manufacturing operations data • Implement real-time and batch processing for enterprise operations data, KPIs, and business metrics • Create data lakehouse architectures optimized for manufacturing analytics and reporting • Develop custom connectors and API integrations for specialized manufacturing equipment and systems • Mentor junior team members and establish data engineering best practices • Collaborate with business stakeholders across various departments to translate requirements into technical solutions • Ensure data governance, security, and compliance within enterprise data environments

• Help define company data assets (data model) • Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage • Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable • Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems • Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way • Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains • Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts