As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.
Alt is unlocking the value of alternative assets, starting with the $5 B trading-card market. We let collectors buy, sell, vault, and finance their cards in one place and we are backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes like Tom Brady and Giannis Antetokounmpo. Our next frontier is real-time pricing at scale—the Alt Value that powers every trade, loan, and product on the platform.
Are you a data engineer who thrives on building robust pipelines and solving complex data challenges? In this role, you'll own Alt's critical data infrastructure that powers our pricing model and marketplace insights by ingesting transaction and listing data from dozens of external marketplaces. You'll be responsible for ensuring our data pipelines deliver fresh, accurate information that drives pricing decisions, market analytics, and business intelligence across the entire platform.
What you'll do here- Design, optimize and own data pipelines that scrape, process and ingest transaction and listing data from major auction houses and marketplaces.
- Build comprehensive monitoring and alerting systems to track latency, uptime, and coverage metrics across all data sources.
- Continuously improve our data infrastructure by modernizing storage and processing technologies, reducing manual interventions, and optimizing for cost, performance, and reliability.
- Partner with internal teams to understand data usage patterns and ensure pipelines deliver clean, standardized data that meets product requirements.
- Care deeply about data quality and understand that extraction is only the beginning - the real value comes from delivering clean and usable data.
- Thrive in a startup environment where you can make immediate impact and own critical systems end-to-end.
- Take an incremental approach to improvements, preferring evidence-based decisions over wholesale replacements.
- Are intellectually curious about how data flows through systems and passionate about automation opportunities.
- Want to work at the intersection of data engineering and product, understanding how your pipelines directly impact business outcomes.
Must-haves:
- 3-4 years of experience in data engineering or related fields
- Strong Python proficiency with at least 3 years of hands-on experience
- Proven experience with large-scale data processing using dataframe technologies (Pandas, Polars, PySpark, or similar)
- Hands-on experience with pipeline orchestration tools (Airflow, Dagster, or similar DAG-based systems)
- Track record of owning at least one data pipeline end-to-end within the past 2 years
- Solid SQL skills for data analysis and transformation
- Previous startup experience - you understand the pace and adaptability required in a fast-moving environment
- A pragmatic mindset focused on delivering value incrementally rather than pursuing perfection
Nice-to-haves:
- Experience with web scraping technologies (Selenium, Puppeteer, Beautiful Soup)
- Familiarity with data infrastructure and cloud services (AWS preferred)
- Interest in or knowledge of trading cards, collectibles, or alternative asset markets
- Experience with LLM-based automation tools for data extraction and processing
- A seat at the table to help shape the future of Alt and the alternative asset space
- Autonomy and ownership on projects that matter
- $100/month work-from-home stipend
- $200/month wellness stipend
- WeWork office stipend
- 401(k) retirement benefits
- Flexible vacation policy
- Generous paid parental leave
- Competitive healthcare benefits, including HSA, for you and your dependent(s)
Base salary range: $155,000–$165,000, plus equity. Offers may vary based on experience, location, and other factors.
ALT San Francisco, California, USA Office
San Francisco, CA, United States
Similar Jobs
.png)
Cloud • Insurance • Payments • Software • Business Intelligence • App development • Big Data Analytics
Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.
Top Skills:
Ansi SqlBigQueryBigquery SqlConfluenceGCPJIRAPythonSQL
Enterprise Web • Mobile • Professional Services • Software
Design, build, and own scalable data pipelines and evaluation systems that power production AI features and internal analytics. Ensure data quality across ingestion, modeling, and reporting, collaborate with ML and analytics teams, deploy and monitor ML systems, and establish standards for data work and evaluation.
Top Skills:
AirflowAWSDagsterGCPPostgresPythonSnowflake
Security • Cybersecurity
Lead design and modernization of scalable, secure data systems and real-time pipelines for xOT cybersecurity. Create data contracts, observability, lineage, and cross-functional solutions supporting cloud and on-prem deployments, Kubernetes, and stream processing to enable threat detection and intelligence.
Top Skills:
CloudData Observability FrameworksDockerGoJvm (Java/Scala/Kotlin)KubernetesMessage QueuesNode.jsOn-PremisesPythonRustStream Processing
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
