Onsite
About Lindy
Lindy is building the AI assistant for everyone else — not the tinkerers, not the builders, but the people who just want their day back. Lindy Assistant lives in iMessage, handles email, calendar, and meetings, and takes two minutes to set up. We're building the layer between powerful AI models and real people's lives.
As Lindy's Data Engineer, you'll work closely with senior leadership (Lindy's CEO, GTM leads, and Head of Engineering) to uncover critical business insights from many sources of in-the-wild data (product analytics, BI/revenue information, customer reports, etc.). You'll be responsible for the end-to-end lifecycle of data, working closely with product and engineering to define key analytics metrics, combining that data into actionable insights, and communicating and disseminating those insights to leadership and across the company.
You'll also be in the driver's seat of our data infrastructure, iterating on Lindy's ETL pipelines, transformed tables, and other fundamental data engineering infrastructure. You'll be collaborating closely with Lindy's Head of Engineering and Director of Ops & Analytics in this capacity. At Lindy, you can expect an environment with little process and high empowerment, paired with high expectations and a strong sense of urgency.
We are an in-office company, working from our downtown San Francisco office 4 days a week. We sponsor visas and cover relocation costs up to $20,000.
Data Infrastructure:
Design and implement scalable ETL pipelines that handle product analytics, customer usage data, and business metrics
Build reliable data warehousing solutions that support both real-time and batch processing needs
Create automated data quality monitoring and alerting systems
Analytics & Insights:
Develop comprehensive dashboards and reporting systems that track key business and product metrics
Collaborate closely with the founder/CEO, PMs, and engineering team to understand customer behavior, product performance, and business health
Identify opportunities to improve lagging metrics across customer acquisition, retention, product adoption, and revenue. Design and implement initiatives to address them
Partner with product and engineering teams to instrument new features with proper analytics tracking
Data Strategy:
Establish frameworks for experimentation and A/B testing across our product
Build self-service analytics capabilities that empower non-technical teams
2+ years of data engineering or data analytics experience (building production data pipelines and analytics infrastructure)
Expert-level SQL skills and experience with modern data warehouses (Snowflake, BigQuery, or similar)
Hands-on experience with ETL tools (Fivetran, Airbyte, or custom solutions) and data transformation frameworks (dbt)
Proficiency with BI tools (Tableau, Looker, or similar) and advanced spreadsheet analysis
Track record of working independently and delivering high-impact projects with minimal oversight
Excitement to work in-person 4 days a week from our downtown San Francisco office
The technical skills of a data-oriented engineer who can build and maintain data infrastructure
The strategic thinking of a business strategist who can identify and communicate our business' most pressing questions
The analytical capabilities of a data analyst who can turn questions and data into insights
Experience with product analytics tools (PostHog, Mixpanel, Amplitude)
Python/JavaScript proficiency for custom analysis and automation
Background in statistics, data science, or machine learning
Previous experience at high-growth B2B SaaS companies
Familiarity with AI/ML product metrics and experimentation
Base Salary Range $150K-$185K + equity
Comprehensive health coverage
$20K relocation assistance and visa sponsorship
High autonomy and direct collaboration with leadership
The fun of working at a no-nonsense 30-person startup that just wants to build an amazing product and business
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