Overview
Senior Analytics Developer Jobs in Kanata, Canada at Canadian AP Ventures Company
Title: Senior Analytics Developer
Company: Canadian AP Ventures Company
Location: Kanata, Canada
Category:
Who We Are…
When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the bringing our characters to life, the bringing them to your living rooms and the creating what’s next…
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN.
To see what it’s like to work at CNN, follow @WBDLife on and !
Your New Role
CNN is seeking a Sr.Analytics Developerwithsubject matterexpertisein analytic workstreamsand data analysis. You havedemonstrateda pattern of independently shippinganalytical solutions. Youare comfortable working oncross-functional team and diverse stakeholder requirements.
Your workpowersaudience analytics, personalization, and contentrecommendations formillions of users dailyacross , the CNN mobile app, and connected TV experiences.
You will drive architecture decisions, set engineering standards, and mentor other engineers on the team. If you thrive on owning complex systems end-to-end and care deeply about building reliable, secure infrastructure at scale — this is the role.
Your Role Accountabilities
Participate inthe architectural direction for CNN’s Data Platform — own data modeling, schema design, and platform capabilities that serve Analytics, Data Science, ML, and AI teams
Develop, design, and implementation ofCNN’s Data Platformfor real-time data use cases
Mentor junior engineers through code reviews, design sessions, and technical guidance
Deliver scalable data pipelines for both real-time streaming and batch processing.
Drive best practices around security, performance, and reliability for data services
Contribute to technical roadmap planning and advocate for improvements to the data platform
Deliver high-quality, well-tested code – improve code, documentation, and operational runbooks with each iteration
Communicate designs, architectural decisions, and technical tradeoffs clearly to engineers and leaders at all levels — represent the data platform domain with autonomy
You create functional level impact and deliver more complex features. You also help driveclarity and define problems proactively.
Evangelize and oversee implementation of data engineering best practices — your code, documentation, and operational standards are the model others follow
You think about the long-term health of your work, your monitoring, your alerting, and your documentation. You nurture all of these in parallel to yourengineerresponsibilities.
Qualifications & Experience
5+ years of software engineering experience with deepexpertisein data engineering, data platform architecture, and large-scale data systems
3+ years of experience withworking with Snowflake, Databricks, or other modern enterprise data warehouses
Experience with data modeling, ETL architecture, and designing schemas that serve diverse analytical and ML use cases
Strong programming experience across at least two of Java, Go, Python, and SQL
Demonstrated experience leading technical directionand influencing best practices
Experience working on end-to-end analytics pipelines from event collection to producing business-ready semantics
Deep familiarity withdbtor similar transformation frameworks
Familiaritywith streaming and event-driven architectures (Kafka, Kinesis, Flink) at scale
Experience building or supporting AI/ML pipelines, feature stores, or model training infrastructure
Familiarity with data governance, data quality frameworks, and data cataloging tools
Experience in media, streaming, digital advertising, or consumer-facing products at scale
How We Get Things Done…
This last bit is probably the most…