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Knowledge of data lifecycle and hands-on experience with application development and AI tooling.

Citylitics Inc.

Data Engineer

Toronto, ON, Canada

$70,000 to $80,000 CAD / year · Full-time

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Job details

Pay: $70,000 to $80,000 CAD / year
Job type: Full-time
Apply by: Mar 31, 2027
Experience: Proven experience (3+ years) working as a Data Engineer or Software Engineer in a cloud environment
Posting language: English
Posted: Oct 2, 2026

Original job description

About Citylitics Inc.

Citylitics delivers predictive intelligence on where, how, and why infrastructure investments will occur across North America.

Infrastructure includes the foundational systems that shape our quality of life: water, transportation, transit, roads and highways, broadband, and power. It represents a multi-trillion-dollar market and a 20+ year megatrend in 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. Leading infrastructure vendors, engineering firms, and construction companies use the platform to identify and pre-position for major infrastructure opportunities earlier, helping them build relationships, shape project priorities, and influence scope before projects move to formal procurement.

Citylitics combines a network of AI agents, fine-tuned models, a proprietary infrastructure signals graph, and daily human-in-the-loop quality assurance workflows to deliver highly nuanced and reliable sales intelligence. The platform integrates seamlessly with CRMs, ERPs, and data lakes, embedding actionable insights directly into sales workflows so teams can prioritize the right pursuits and build stronger pipelines.

Our mission is to improve how infrastructure investments get made so critical needs can be addressed earlier and communities benefit from stronger, more resilient infrastructure.

Join Citylitics to work in a meaningful industry that will matter for decades to come while helping grow a company at the forefront of applied AI. We operate with a Results-Driven Mentality and a commitment to Raise The Bar, in a collaborative environment where Teamwork Makes the Dream Work as we tackle big challenges and celebrate wins together.

Who Are We Looking For?

We're looking for a skilled and enthusiastic Data Engineer to join our growing team! We're a close-knit group building and maintaining mission-critical data products, and we need someone who can hit the ground running.

This role requires a strong command of data engineering best practices, a track record with orchestration and data warehouses, and hands-on experience shipping LLM and agentic workflows to production. You'll own the design, build, and operation of production data pipelines that use AI to power customer-facing solutions. You'll work with technologies we already use, including GCP services like Cloud Composer, Cloud SQL, BigQuery, and Vertex AI.

Beyond the technical skills, we value collaboration, sound engineering judgment, and the ability to adapt as AI tooling changes fast. If you're passionate about data, have put AI into production and want to do more of it, and are excited by impactful projects, we encourage you to apply.

This is a hybrid role based out of Citylitics' Toronto office and requires 3+ days in-office per week.

What Will You Accomplish? / How You Will Make An Immediate Impact:

Pipeline Orchestration: Lead the development of highly performant, reliable, and maintainable pipelines using Airflow and BigQuery, from architecture and design through testing, deployment, monitoring, and maintenance. You'll make design decisions independently and own the systems you build
Data Modeling & Dashboards: Partner with data analysts and stakeholders to define requirements and design scalable data models and applications. You'll own data products end to end, from the pipelines and models through the backend APIs to the customer-facing dashboards and apps built on them
AI & Agentic Workflows: Design and operate pipelines that use LLMs and agents to turn raw documents into structured, useful data. This includes prompt and context design, tool and function calling, embeddings and retrieval, structured outputs, and production concerns like retries, idempotency, cost, and latency. You'll also own evaluation datasets, LLM-as-judge and rule-based QA checks, and benchmarks that turn results into clear decisions about models, prompts, and architecture
Continuous Improvement: Drive the ongoing improvement of our data infrastructure and processes, including evaluating and introducing new technologies and best practices. We're an AI-first team that uses coding agents like Claude Code daily for development, debugging, review, and documentation, and we're looking for someone who can help shape how we push that further
Other duties as assigned

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) and their production tradeoffs, such as cost, latency, and failure modes
Daily, fluent use of AI coding agents (e.g., Claude Code, Cursor) in your workflow, with the judgment to review and verify what they produce
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
Excellent problem-solving skills and the ability to work independently on ambiguous problems
Excellent communication and collaboration skills. You'll be working closely with analysts, product, and other stakeholders

Vacancy Status: This position is for an existing and active vacancy that the company is currently seeking to fill.

Benefits

What's in it for you?

Make real-world impact: Influence positive change across one of the biggest societal challenges of our generation: building and maintaining sustainable public infrastructure
Sell a genuinely differentiated platform: You'll represent a disruptive, data-driven solution with a compelling value proposition in a market that is eager to engage
Operate at the intersection of infrastructure, scale-up, and data science: We live where infrastructure meets AI and advanced data. There is no other team like ours in Toronto
Move fast, learn faster: There's no corporate bureaucracy here. You'll accomplish more in a few months than you would in years at a large, entrenched technology company
Be empowered by data and AI: We believe Data and AI will play an outsized role in the future of sales and decision-making. Every CityZen has access to generative AI tools and our full data universe to enhance productivity and encourage experimentation
Grow with intention: We invest deeply in our people through in-role coaching, skill-based development, and clear internal promotion pathways
Win as a team: We work hard, we support one another, and we celebrate progress along the way. We're serious about solving infrastructure and just as serious about enjoying the journey together

Citylitics is an equal opportunity employer. We are passionate about providing a safe workplace where everyone is accepted and has the opportunity to grow with us. We are committed to making diversity and inclusivity part of our culture!

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More about this job

Responsibilities

Design, build, operate, and maintain reliable production data pipelines and scalable data products, including data models, backend APIs, and customer-facing dashboards. Develop and evaluate LLM- and agent-powered workflows that transform documents into structured data, while improving infrastructure, quality assurance, and engineering practices.

Requirements

Requires 3 or more years of data or software engineering experience, proficiency in Python and SQL, and production experience with orchestrated pipelines, data warehouses, and cloud platforms, preferably GCP. Candidates should have shipped LLM-powered features or pipelines, understand agent and retrieval patterns and their production tradeoffs, use AI coding agents fluently, and communicate and collaborate effectively.

Skills

Python
SQL
Data Engineering
Apache Airflow
Google Cloud Composer
BigQuery
Data Modeling
ETL/ELT
Data Pipeline Orchestration
LLM Integration
Agentic Workflows
Prompt Engineering
Retrieval-Augmented Generation
Git
CI/CD
Backend API Development

Benefits

Professional Development
In-Role Coaching
Skill-Based Development
Internal Promotion Pathways
Access to Generative AI Tools

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Google Cloud Platform
Cloud Composer
Cloud SQL
BigQuery
Vertex AI
Apache Airflow
Data Engineering
Data Pipelines
ETL/ELT
Data Modeling
LLMs
Gemini
Claude
OpenAI
Prompt Engineering
Structured Outputs
Tool Calling
Agentic Workflows
Retrieval-Augmented Generation
Embeddings
MCP
Git
CI/CD
React
TypeScript
Backend APIs
Data Warehouses
Evaluation Datasets

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