Director, DevOps Insights

RBC; Toronto; On-site; CAD 180,000 - 240,000; Full time

Benefits offered by this job

Total Rewards Program

Bonuses and stock where applicable

Job summary

RBC is seeking a Director, DevOps Insights in Toronto to lead a data engineering and data science team that turns telemetry from the software lifecycle into executive insights. You will own the Tokenomics model forecasting AI spend and drive productivity insights.

You will build self-serve reporting, collaborate with Finance and platform owners, and apply AI coding agents to RBC pipelines in a regulated banking environment.

Qualifications

• 10+ years in data engineering, data science or software development with 3+ years in director-level leadership
• Experience coaching and growing data teams
• Hands-on use of AI coding agents in daily work
• Strong background in Python, SQL, Snowflake, Airflow and cloud data platforms
• Experience turning telemetry into metrics for senior audiences; familiarity with DORA/SPACE frameworks
• Experience with cost analysis or forecasting of technology spend with executives

Responsibilities

• Lead and grow a data engineering and data science team; set clear goals and paths for growth
• Own the developer data platform roadmap for telemetry ingestion, modeling and serving tools
• Define metrics and reporting standards used bank-wide (DORA, SPACE, RBC measures)
• Deliver Tokenomics and productivity insights; forecast AI tooling spend and report to leadership

Skills

Data engineering

Data Science

Python

SQL

Leadership

AI coding agents

Cost forecasting

Cloud platforms

DORA/SPACE experience

Stakeholder communication

Tools

Snowflake

Airflow

Cloud infrastructure

Job description

Job Description

What is the opportunity?

RBC's DevOps team owns the data behind how our engineers work: the telemetry from every tool in the software development lifecycle, from source control and CI/CD through to the AI coding assistants developers now use every day. As Director, DevOps Insights, you'll lead the data engineering and data science team that turns this telemetry into answers senior and executive leadership act on. What is AI adoption costing us, what is it returning, where is developer productivity improving, and where is it stuck? You'll own the Tokenomics model that forecasts AI spend across engineering and the productivity measurement that shows whether the investment is paying off. This is a hands-on leadership role for someone who uses AI coding agents daily and wants to lead a team that does the same

What will you do?

Lead and grow the team

• Manage, coach and develop a team of data engineers and data scientists, setting clear goals and creating growth paths for each person
• Build a team culture where AI agents are part of everyday engineering and analysis work, and where output quality is measured
• Prioritize the team's work against the highest-value questions from leadership, Finance and engineering teams

Own the developer data platform

• Set the roadmap for ingesting, modelling and serving telemetry from the tools developers use: source control, CI/CD, work tracking, IDEs, AI coding assistants and cloud platforms
• Direct the engineering of pipelines on Snowflake, Airflow and Python, with the reliability and data quality standards a bank requires
• Establish the metrics definitions (DORA, SPACE and RBC-specific measures) used across RBC

Deliver Tokenomics and productivity insights

• Own the cost attribution and forecasting model for AI tooling usage across engineering, and report it to executive leadership and Finance
• Produce the analysis that shapes AI usage policy and provides input to vendor negotiations
• Quantify developer productivity and the benefits of AI adoption, and present findings that lead to decisions
• Build self-serve reporting so teams and leaders can answer routine questions without the team in the loop

Apply AI to the work

• Use AI coding agents and analytical tools in the team's own pipelines, analysis and reporting, and set the standard for how they're used
• Evaluate model cost and quality trade-offs when applying LLMs to insights problems

Partner across the bank

• Work with Finance on spend forecasting and budget planning for AI and developer tooling
• Partner with platform owners and engineering leaders to close data gaps and validate findings
• Present to senior and executive audiences with clear recommendations

What do you need to succeed

Must Have

• Minimum 10+ years in data engineering, data science or software development, with 3+ years in director-level or equivalent leadership roles
• People management experience leading data engineers and/or data scientists, with a record of coaching and growing individuals
• Daily hands-on use of AI coding agents in your own work, and the ability to discuss in detail how you use them, where they fail and how you check their output
• Strong data engineering background: Python, SQL, Snowflake, Airflow and cloud data platforms
• Experience turning operational telemetry into metrics and insights for senior audiences; familiarity with DORA, SPACE or comparable frameworks
• Experience with cost analysis or forecasting of technology spend, presented to executives and finance partners
• Ability to prioritize competing demands against a small team's capacity and to influence without direct authority

Nice to have

• Shipped an LLM-based capability into production
• Led AI adoption across an engineering or analytics team and measured its results
• Experience shaping usage policy or contributing to vendor negotiations for developer or AI tooling
• Data science depth: statistical analysis, experimentation and forecasting models
• Experience working in a large regulated organization, such as a bank

What's in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• Flexible work/life balance options

#LI-post

#TECHPJ

Job Skills

Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Quality Management, Requirements Analysis, Software Product Management, Waterfall Model

Additional Job Details

Address:

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-09-9

Application Deadline:

2026-09-28

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.