Role: Senior Data Engineer

Location: Santa Monica, CA (Hybrid)

Our client is redefining how brands connect with the next generation of talent and consumers.

With over 500,000 Gen Z students across every major U.S. campus and 1,000+ brand partners, they’re building a leading platform where students turn creativity into opportunity—and where brands authentically show up on campus and online.

They’re in a stage of rapid growth, backed by top-tier investors, and are looking for a Senior Data Engineer to join and help shape the next chapter. This role will sit on their Engineering Team, reporting directly to the Head of Engineering.

Position Overview:

They are seeking a Senior Data Engineer to help power the core product experiences of their marketplace platform. This is a highly product-focused data engineering role centered on search, matching, and recommendation systems that connect companies with gig workers.

Data Engineering is foundational to how their platform works. Both sides of the marketplace rely on data-driven discovery, matching, and suggestions. As a Senior Data Engineer, you’ll focus on improving the quality, reliability, and scalability of the data systems that directly impact these user-facing features.

You’ll work closely with Engineering, Product, Design, and the COO to translate business and product goals into data systems that meaningfully improve user outcomes — not just internal reporting.

This role is best suited for someone who has experience in a consumer tech or marketplace startup and wants to work close to the product surface area.

Key Responsibilities:

• Design, build, and improve data systems that power search, matching, and recommendation features across the marketplace.
• Partner with product and engineering teams to define data requirements that directly support user-facing functionality.
• Build and maintain scalable ETL/ELT pipelines that prioritize data quality, freshness, and reliability.
• Implement monitoring, validation, and alerting to ensure high-confidence data at scale.
• Model and manage data used by application services, analytics, and machine learning workflows.
• Improve the performance and availability of data systems that support real-time or near–real-time use cases.
• Develop reusable tooling and frameworks that make it easier for teams to build on top of shared data systems.
• Document data models, pipelines, and system behavior to support long-term maintainability.
• This role is intentionally not focused on dashboards or ad hoc reporting requests.

Qualifications:

• Must-Have
• 6–8+ years of experience in data engineering, software engineering, or closely related roles.
• Strong product mindset — experience working on systems that directly impact end users or product features.
• Proficiency in SQL and data modeling for production systems.
• Experience building or supporting search, matching, or recommendation systems.
• Hands-on experience with Elasticsearch or similar search technologies.
• Experience with modern data platforms (e.g., Snowflake, BigQuery, Redshift).
• Familiarity with data orchestration tools such as Airflow, dbt, or Luigi.
• Experience working with cloud platforms (AWS or GCP) for deploying and operating data systems.
• Cloud & Infrastructure Clarity
• Cloud experience is focused on building and operating data systems, not owning all infrastructure, security, or DevOps.
• Deep expertise in Terraform, networking, or security tooling is not required.
• Nice-to-Have
• Experience with marketplace or consumer-facing products.
• Exposure to recommendation systems, ranking, or ML-adjacent workflows.
• Familiarity with CI/CD or DevOps practices.
• Experience with data quality, lineage, or governance tools.
• Working knowledge of Node.js.
• Based in Los Angeles and able to work hybrid in-office.

What they Offer:

• Competitive annual base compensation
• Equity Option Award Compensation
• Health, Dental, and Vision Insurance
• 401(k) Plan
• Unlimited PTO
• Laptop and WFH setup reimbursement
• Hybrid office environment in Santa Monica