Senior Data Engineer

Stack

Responsibilities

• ▹Design, build, and own end-to-end data pipelines and transformation workflows using dbt on BigQuery
• ▹Develop scalable ELT models supporting analytics, AI, marketing, and operational use cases
• ▹Take ownership of existing pipelines while improving their reliability, maintainability, and performance
• ▹Orchestrate and schedule data workflows using Dagster, ensuring pipelines are reliable, observable, and easy to operate
• ▹Build robust testing, monitoring, alerting, and recovery processes across the data platform
• ▹Improve pipeline architecture as workloads, data volumes, and business-critical use cases grow
• ▹Partner with analysts and data scientists to deliver trusted, well-modeled, self-serve datasets in Hex
• ▹Integrate and operationalize AI and LLM-driven workflows within the data platform
• ▹Help internal teams move from ad-hoc data requests to scalable and reusable data products
• ▹Build marketing attribution models that improve visibility into campaign performance and conversion
• ▹Develop reverse ETL workflows that send accurate conversion data back to platforms such as Google Ads and Meta
• ▹Integrate external data sources, advertising APIs, and data vendors into reliable production pipelines
• ▹Establish and enforce standards for data quality, testing, documentation, observability, and deployment
• ▹Optimize BigQuery workloads for query performance, scalability, and cost efficiency
• ▹Contribute to data architecture decisions, mentor future hires, and help shape technical direction

Requirements

• ▹Advanced SQL skills and hands-on experience building production-grade data pipelines
• ▹Production experience designing, maintaining, and optimizing data workflows using dbt and BigQuery
• ▹Experience using Dagster or a comparable tool such as Airflow or Prefect to orchestrate production workflows
• ▹Comfortable using Python to build pipelines, automate processes, and develop data engineering tools
• ▹Understanding of dimensional modeling, ELT patterns, and designing datasets for reliability, usability, and scale
• ▹Experience applying version control, automated testing, and deployment practices (Git, CI/CD) to data workflows
• ▹Comfortable working in an AI-driven environment and interested in applying LLMs to real data problems

Nice to have

• ▹Experience with Hex or a similar notebook/BI tool such as Looker, Mode, or Tableau
• ▹Experience integrating LLM APIs or building AI-powered data products and workflows
• ▹Hands-on experience with Dagster assets, sensors, partitions, and production deployment patterns
• ▹Experience with streaming technologies such as Pub/Sub, Kafka, or Dataflow
• ▹Experience with data governance: access controls, lineage, or warehouse cost management
• ▹Experience building attribution models or working with conversion APIs / reverse ETL tools such as Hightouch or Census

What we offer

• ▹Competitive compensation
• ▹Equity ownership
• ▹30 vacation days in Europe; 20 vacation days plus 8 sick days in the US, plus public holidays
• ▹Health & wellness benefits per local country norms (Europe); multiple low-premium medical plans plus dental and vision coverage (US)
• ▹Pension contributions per local country norms (Europe); 401(k) with 4% employer match (US)
• ▹Company-paid short-term and long-term disability insurance plus life insurance (US)
• ▹€1K (or equivalent) per year for courses, books, events, or coaching
• ▹Regular hackathons
• ▹Remote-first work with regular team off-sites in Europe
• ▹$100/month to support open source projects
• ▹Unlimited AI tooling budget

About the company

n8n is an open workflow orchestration platform built for the AI era. The team has grown to 260+ people across Europe and the US, with its center of gravity in Berlin. It has cultivated a community of 650,000+ active developers, earned 190K+ GitHub stars, and is valued at $5.2bn with investors including Sequoia and SAP.