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Salary: USD 180,000 - 220,000 / annual
You.com is building the AI Search Infrastructure that powers modern AI systems, creating a trusted knowledge layer for agents, applications, and enterprises to retrieve real-time, accurate, and citation-backed information. The platform combines proprietary vertical indexes with LLM-optimized retrieval systems.
As a Data Engineer, you will be a hands-on contributor building and scaling the modern data platform. You'll work closely with Finance, Engineering, Product, and Analytics teams to develop reliable, high-performance data pipelines and systems supporting both batch and real-time data processing. Your work will enable data activation, ensuring high-quality data flows into the warehouse and outward to business tools like Salesforce, while powering next-generation AI-driven applications including agent-based systems.
Key responsibilities include:
- Building and maintaining scalable data pipelines (batch and streaming) using Databricks, Spark, Kafka, and AWS services
- Developing pipelines from source systems (Salesforce, billing, product events, API logs) into clean analytics layers
- Designing and optimizing ETL/ELT workflows using DBT, PySpark, and SQL
- Partnering with Finance on revenue accounting, COGS, margin reporting, and forecasting models
- Enabling marketing and growth data use cases such as segmentation, campaign targeting, and lifecycle analytics
- Developing reverse ETL pipelines to sync data from the warehouse to tools like Salesforce, HubSpot, and Braze
- Creating curated datasets to support analytics, reporting, and go-to-market initiatives
- Building dashboards and reporting layers for marketing and business performance tracking
- Supporting AI/ML and agent-based applications by preparing datasets for MCP integrations and AI-driven applications
- Monitoring pipeline performance, troubleshooting issues, and ensuring data reliability and quality
- Implementing data quality checks, validations, and alerting mechanisms
- Collaborating with cross-functional teams to define data contracts and ensure consistency
Requirements:
- 6+ years of experience in data engineering or 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 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 (strong plus)
- Experience working with Finance and building finance-specific metrics and pipelines (strong plus)
- Understanding of data modeling and working with large-scale datasets (batch and streaming)
- Experience creating dashboards and supporting reporting workflows using BI tools
- Strong problem-solving skills and ability to debug production data issues
- Strong communication skills and ability to work collaboratively across teams
