Data Engineer - Lindy

Data Engineer - Lindy Lindy is building the layer between powerful AI models and real people's lives; an AI Assistant for everyone else — not the tinkerers, not the builders, but the people who just want their day back. Apply About The Role 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, large volumes of unstructured data, and more). 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 own how Lindy turns raw data into something the whole company can use. A lot of our most valuable information is unstructured text in MongoDB and finance data that comes in messy, and you'll shape it into clean, reliable tables teams across the company depend on. 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. Key Responsibilities Data Infrastructure: Design and implement scalable ETL pipelines that handle product analytics, customer usage data, and business metrics Wrangle large volumes of unstructured and semi-structured data, including unstructured text from MongoDB and finance data, into clean, queryable tables 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). We run Snowflake. Proficiency in Python Hands-on experience with ETL tools (Fivetran, Airbyte, or custom solutions) and data transformation frameworks (dbt). Our stack is Fivetran and dbt. Experience working with large, unstructured datasets, or a strong aptitude and genuine appetite to learn it fast. This is the heart of the role. Working knowledge of elementary statistics (averages, percentiles, basic descriptive analysis) 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 Ability to work in-person 4 days a week from our downtown San Francisco office You'll bring 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 Familiarity with the basics of machine learning: knowing what a linear regression is and how to interpret model output Direct experience working with finance data Compensation and Benefits Base Salary Range $170K-$240K + equity Comprehensive health coverage $20K relocation assistance and visa sponsorship High autonomy and direct collaboration with leadership Department Operations Locations SF Office About Lindy An iMessage-native AI assistant that gives you 2+ hours back every day by handling your inbox, meetings, and calendar proactively. Founded in 2023 Coworkers 22