About the company
Citylitics delivers predictive intelligence on where, how, and why infrastructure investments will occur across North America. Citylitics transforms millions of documents across more than 40,000 cities, utilities, and public agencies into real-time market signals and high-value sales intelligence.
Responsibilities
- Lead the development of highly performant, reliable, and maintainable pipelines using Airflow and BigQuery, from architecture and design through testing, deployment, monitoring, and maintenance
- Partner with data analysts and stakeholders to define requirements and design scalable data models and applications
- Design and operate pipelines that use LLMs and agents to turn raw documents into structured, useful data
- Own evaluation datasets, LLM-as-judge and rule-based QA checks, and benchmarks
- Drive the ongoing improvement of our data infrastructure and processes
Requirements
- Proficiency in Python and SQL
- Proven experience (3+ years) working as a Data Engineer or Software Engineer in a cloud environment
- Experience building production data pipelines with an orchestrator like Airflow/Cloud Composer and a data warehouse like BigQuery
- Solid grasp of data engineering fundamentals: data modeling, ETL/ELT, and building idempotent, reliable pipelines
- Experience shipping LLM-powered features or pipelines to production with LLM APIs (e.g., Gemini, Claude, OpenAI): prompting, structured outputs, and tool/function calling
- Working knowledge of agent patterns (tool use, multi-step workflows, retrieval/RAG, MCP)
- Daily, fluent use of AI coding agents (e.g., Claude Code, Cursor)
- Experience with Git, CI/CD, and cloud platforms (GCP preferred)
- Experience building data apps or dashboards end to end, including a backend API and a frontend (e.g., React, TypeScript), is a plus
Conditions
- This is a hybrid role based out of Citylitics' Toronto office and requires 3+ days in-office per week