Data Engineer

Lindy; San Francisco (CA); On-site; USD 150,000 - 185,000; Full time

Benefits offered by this job

Comprehensive health coverage

Equity options

$20K relocation assistance

High autonomy in work

Job summary

A tech startup in San Francisco is seeking a Data Engineer to design ETL pipelines, develop analytics systems, and ensure data quality. The role offers collaboration with leadership and a focus on impactful data-driven insights. Candidates should have 2+ years of experience, expertise in SQL, and familiarity with ETL tools like Fivetran and BI tools like Tableau. Competitive salary range of $150K-$185K plus equity and relocation assistance offered for the right candidate.

Qualifications

• 2+ years of data engineering or data analytics experience.
• Expert-level SQL skills.
• Hands-on experience with ETL tools and data transformation frameworks.
• Proficiency with BI tools and advanced spreadsheet analysis.
• Ability to work independently and deliver high-impact projects.

Responsibilities

• Design and implement scalable ETL pipelines.
• Build reliable data warehousing solutions.
• Create automated data quality monitoring systems.
• Develop dashboards tracking key business metrics.
• Collaborate to understand customer behavior.
• Establish frameworks for experimentation across products.

Skills

Data engineering

SQL

ETL tools

BI tools

Data analysis

Tools

Snowflake

BigQuery

Fivetran

Airbyte

Tableau

Looker

Job description

Overview

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.

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.

Position 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.

Work Location 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.

Key Responsibilities

• 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

Must haves

• 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

Nice to have

• 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

Compensation And Benefits

• 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