Data Engineer

Citylitics Inc.

. Lead development of performant, reliable, and maintainable data pipelines using Airflow and BigQuery .

Posted 10/3/2026full-timeToronto • CanadaMid-LevelSenior💰 CA$90,000 - CA$110,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining data pipelines using Airflow and BigQuery, with a strong focus on data modeling, ETL/ELT processes, and LLM-powered features. Proficient in Python and SQL, with a solid understanding of production tradeoffs and the use of AI coding agents.

Highest-signal resume keywords

Python ProficiencySQL ProficiencyAirflow/Cloud Composer ExperienceLLM API ExperienceData Modeling Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentETL/ELT ProcessesIdempotent PipelinesPrompting TechniquesStructured OutputsTool/Function CallingData Infrastructure ImprovementProduction MonitoringData App DevelopmentBackend API Development

Soft Skills

Problem-SolvingIndependent WorkingCommunicationCollaboration

Tools & Technologies

AirflowBigQueryGCPGitCI/CDReactTypeScriptAI Coding Agents

Industry Keywords

Data EngineeringSoftware EngineeringCloud EnvironmentLLM-Powered FeaturesProduction Tradeoffs

Tech Stack

Tools & technologies

AirflowBigQueryCloudETLGoogle Cloud PlatformPythonReactSQLTypeScript

About the role

Key responsibilities & impact

Lead development of performant, reliable, and maintainable data pipelines using Airflow and BigQuery
Own pipeline architecture, design, testing, deployment, monitoring, and maintenance
Make independent design decisions and operate the systems built
Partner with data analysts and stakeholders to define requirements and design scalable data models and applications
Own data products end to end, including pipelines, models, backend APIs, customer-facing dashboards, and applications
Design and operate AI and agentic workflows that transform raw documents into structured data
Develop prompts and context, tool/function calling, embeddings and retrieval, and structured outputs
Manage production concerns including retries, idempotency, cost, and latency
Own evaluation datasets, LLM-as-judge and rule-based QA checks, and benchmarks
Use evaluation results to guide decisions about models, prompts, and architecture
Continuously improve data infrastructure and processes
Evaluate and introduce new technologies and best practices
Help shape the use of AI coding agents for development, debugging, review, and documentation
Perform other duties as assigned

Requirements

What you’ll need

Proficiency in Python and SQL
3+ years of experience as a Data Engineer or Software Engineer in a cloud environment
Experience building production data pipelines with Airflow/Cloud Composer and BigQuery
Knowledge of data modeling, ETL/ELT, and idempotent, reliable pipelines
Experience shipping LLM-powered features or pipelines to production using LLM APIs such as Gemini, Claude, or OpenAI
Experience with prompting, structured outputs, and tool/function calling
Working knowledge of agent patterns including tool use, multi-step workflows, retrieval/RAG, and MCP
Understanding of production tradeoffs including cost, latency, and failure modes
Daily, fluent use of AI coding agents such as Claude Code or Cursor, with ability to review and verify outputs
Experience with Git, CI/CD, and cloud platforms; GCP preferred
Experience building end-to-end data apps or dashboards with backend APIs and frontends such as React and TypeScript is a plus
Excellent problem-solving, independent working, communication, and collaboration skills

Benefits

Comp & perks

Make real-world impact by influencing sustainable public infrastructure
Represent a differentiated, data-driven infrastructure platform
Work at the intersection of infrastructure, scale-up, and data science
Fast-paced environment with minimal corporate bureaucracy
Access to generative AI tools and the company’s full data universe
In-role coaching, skill-based development, and clear internal promotion pathways
Collaborative team environment with shared celebrations and support
Safe, diverse, and inclusive workplace
Equal opportunity employer