Data Engineer

Ai, Inc
San Francisco, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$180,000.0 - $220,000.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Airflow Amazon Web Services Amazon S3 Big Data Information Engineering Extract Transform Load (ETL) Data Systems Software Debugging Python (Programming Language) Operational Databases
+11 more
Salesforce.Com SQL Databases Systems Integration Data Ingestion Large Language Models Apache Spark Pyspark Apache Kafka Hubspot Data Pipelines Databricks

Job description

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 Finance, 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, kafka and several 3rd party data, 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 such as Salesforce etc. Additionally, you will help power next-generation AI-driven applications, including agent-based systems and AI driven tools using OSS tech, 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., * Build and maintain scalable data pipelines (batch and streaming) using tools such as Databricks, Spark, Kafka, and AWS services

  • Build and maintain pipelines from source systems (Salesforce, billing, product events, API logs) into clean analytics layers
  • Design, develop, and optimize ETL/ELT workflows using DBT, PySpark, SQL, and tools like Fivetran
  • Work closely with finance in developing Finance data solutions, Finance metrics and forecasting models
  • Partner with Finance on revenue accounting, COGS, and margin reporting
  • 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 MCP (Model Context Protocol) integrations and AI driven applications
  • 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

Requirements

  • 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 Finance and building finance specific metrics and pipelines is a strong plus
  • 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

Benefits & conditions

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 $180,000-$220,000 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

About the company

At You.com, we’re thoughtful about how we use AI throughout our business - including our hiring process.

During certain stages of the interview process, we may use AI-powered tools to assist with administrative tasks such as scheduling, note-taking, transcription, or summarizing interview discussions. These tools are intended to support our interviewers by improving accuracy and efficiency - they do not make hiring decisions or replace human judgment.

All employment decisions are made by our recruiting team and hiring managers based on a holistic review of each candidate and applicable evaluation criteria.

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