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

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 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

Benefits

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringETLELTPythonPySparkSQLdata modelingdata quality checksdata ingestionAI/ML data pipelines

Soft Skills

problem-solvingcommunicationcollaboration