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Data Engineer

San Francisco (Hybrid)

About Us

At You.com, we are building the AI Search Infrastructure that powers modern AI systems. Our goal is to create the trusted knowledge layer that agents, applications, and enterprises rely on to retrieve real-time, accurate, and citation-backed information.

Our platform combines proprietary vertical indexes with LLM-optimized retrieval systems to power AI agents, applications, and enterprise workflows. We are solving hard problems across search, large language models, and large-scale infrastructure to make AI systems more reliable, transparent, and useful.

Our team includes engineers, researchers, product builders, and operators who care about solving meaningful problems and delivering real-world impact. Whether you are improving core infrastructure, shaping product experiences, or helping bring new AI capabilities to market, your work will help define how modern AI finds and uses knowledge.

About the Role

We are looking for a hands-on Data Engineer to help build and scale our modern data platform. In this role, you will work closely with engineering, product, and analytics teams to develop reliable, high-performance data pipelines and systems.

You’ll contribute to both batch and real-time data processing using technologies like Databricks, AWS, and Kafka, while helping ensure data quality, accessibility, and usability across the organization. You’ll play a key role in enabling data activation, ensuring that high-quality data flows not only into the warehouse but also outward to business tools like Salesforce, HubSpot, and Braze. Additionally, you will help power next-generation AI-driven applications, including agent-based systems and retrieval-augmented generation (RAG), by building robust data foundations and pipelines. This is a great opportunity for someone who enjoys solving data challenges end-to-end from ingestion to insights.

Responsibilities

  • Build and maintain scalable data pipelines (batch and streaming) using tools like Databricks, Spark, Kafka, and AWS services
  • Design, develop, and optimize ETL/ELT workflows using DBT, PySpark, SQL, and tools like Fivetran
  • Partner closely with marketing and growth teams to enable data use cases such as segmentation, campaign targeting, and lifecycle analytics
  • Develop and maintain reverse ETL pipelines to sync data from the warehouse to tools like Salesforce, HubSpot, Braze, and other downstream systems
  • Create and manage curated datasets to support analytics, reporting, and go-to-market initiatives
  • Build and maintain dashboards and reporting layers to support marketing and business performance tracking
  • Support AI/ML and agent-based applications by preparing and serving high-quality datasets for RAG pipelines and MCP (Model Context Protocol) integrations
  • Monitor pipeline performance, troubleshoot issues, and ensure high data reliability and quality
  • Implement data quality checks, validations, and alerting mechanisms across both ingestion and activation layers
  • Collaborate with cross-functional teams to define data contracts and ensure consistency across systems

Qualifications

  • 6+ years of experience in data engineering or a related field
  • Strong hands-on experience with Databricks, AWS (S3, Glue, Athena, EMR, etc.), and Kafka
  • Proficiency in Python (PySpark) and SQL for large-scale data processing
  • Experience building and maintaining ETL/ELT pipelines (DBT/Airflow or similar experience preferred)
  • Experience with data ingestion tools such as Fivetran (or similar)
  • Familiarity with reverse ETL / data activation workflows and syncing data to tools like Salesforce, HubSpot, Braze
  • Exposure to or experience with AI/ML data pipelines, including RAG architectures, vector databases, or embeddings workflows
  • Familiarity with agent-based systems, MCP integrations, or LLM-powered applications is a strong plus
  • Experience working with marketing, Product or growth teams on data use cases (segmentation, attribution, campaign analytics, etc.)
  • Understanding of data modeling and working with large-scale datasets (batch and streaming)
  • Experience creating dashboards and supporting reporting workflows (BI tools) for both internal and external audiences
  • Strong problem-solving skills and ability to debug production data issues
  • Strong communication skills and ability to work collaboratively across teams
  •  

Our salary bands are structured based on a combination of geographic tiers and internal leveling. Compensation is determined by multiple factors assessed during the interview process, with the final offer reflecting these considerations.

Salary Band

$185,000 - $225,000 USD

Company Perks:

  • Hubs in San Francisco and New York City offering regular in-person gatherings and co-working sessions

  • Flexible PTO with U.S. holidays observed and a week shutdown in December to rest and recharge*

  • A competitive health insurance plan covers 100% of the policyholder and 75% for dependents*

  • 12 weeks of paid parental leave in the US*

  • 401k program, 3% match - vested immediately!*

  • $500 work-from-home stipend to be used up to a year of your start date*

  • $600 technology stipend to support a portion of our hybrid/remote team's cell phone and internet expenses*

  • $1,200 per year Health & Wellness Allowance to support your personal goals*

  • The chance to collaborate with a team at the forefront of AI research

*Certain perks and benefits are limited to full-time employees only

You.com participates in E-Verify. We will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s Form I-9 to confirm work authorization. (English/Spanish: E-Verify Participation/Right to Work) We are also an inclusive, equitable, and accessible workplace. Please let us know if you require accommodation for any portion of the recruitment and hiring process.

Beware of recruiting scams: You.com will only contact you through official @You.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

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