At Index Exchange, we’re reinventing how digital advertising works—at scale. As a global advertising supply-side platform, we empower the world’s leading media owners and marketers to thrive in a programmatic, privacy-first ecosystem. Our platform is vertically integrated from servers to networks and runs primarily on our own metal and cloud infrastructure.

At the core of it all is our engineering-first culture. From moving petabytes of data and optimizing with AI to making real-time infrastructure decisions, Indexers have the agency and influence to shape the future of advertising.

Index

Exchange is looking for an experienced Engineering Manager / Engineering Lead to lead a team building the data products that turn large-scale marketplace data into capabilities consumed by customers, internal applications, operational teams, and machine learning systems.

Our Data

Products organization sits between foundational data infrastructure and the consumers of data. We build the curated datasets, real-time data products, domain APIs, reporting experiences, integrations, and delivery mechanisms that make data usable as a product. This is a highly technical leadership role.

You will lead and develop a team of engineers while helping define the architecture and technical direction of systems spanning large-scale data processing, distributed systems, APIs, streaming, analytics, and product-facing serving. The ideal candidate combines strong engineering leadership with deep technical experience building data-intensive products and distributed backend systems at scale . Lead a High-Impact Engineering Team Lead, mentor, and grow engineers working across backend systems, data processing, APIs, streaming, and analytical products.

Establish strong engineering practices around architecture, testing, reliability, observability, operational ownership, and system design. Create an environment where senior engineers can independently lead complex technical initiatives. Partner with Product and Engineering leadership to translate business needs into a scalable technical roadmap.

Balance near‑product delivery with investments in architecture, automation, reliability, and engineering velocity.

Build

Data as a Product Lead the development of reusable data products that turn large-scale marketplace data into trusted business capabilities. Build curated and aggregated datasets supporting reporting, billing, operational workflows, experimentation, and ML use cases. Establish reusable aggregation frameworks and standardized patterns for creating new data products. Drive self‑service patterns that reduce one‑off engineering work and make data capabilities reusable across the organization.

Build

Real‑Time Data Products Help evolve Data Products beyond traditional batch analytics toward increasingly real‑time product experiences. Build streaming‑derived datasets and real‑time operational data products. Design business‑oriented transformations and aggregations over high‑volume event streams.

Develop architectures that combine historical and real‑time data where appropriate.



Work with shared streaming and data platform teams while owning the business‑facing products built on top of those capabilities. Build APIs & Serving Experiences Data should be accessible as a product rather than only through databases or BI tools.

You will help lead the development of: Domain‑oriented data APIs. High‑performance reporting and retrieval APIs. Serving layers combining historical and real‑time datasets. Semantic and product‑oriented data access patterns.

API‑first interfaces that allow applications and services to consume data without understanding the underlying data infrastructure. You will drive clear contracts between producers and consumers and ensure these systems remain reliable as data volumes and use cases grow. Lead the evolution of customer‑facing and operational analytics from tightly coupled BI architectures toward more flexible API‑first and serving‑first experiences .

Customer‑facing reporting products. Architectures that separate data products and semantic definitions from individual visualization technologies.

Build

Integrations & Data Distribution Capabilities Enable data to move reliably beyond the systems where it is generated. Build standardized integration patterns using APIs, event streams, connectors, webhooks, and external delivery pipelines. Develop scalable customer and partner data delivery capabilities.

Support patterns such as data sharing, Reverse ETL, and API‑based distribution. Drive self‑service consumption patterns for downstream applications, partners, operational systems, and ML consumers. Enable AI & ML Data Products Partner with ML and product teams to make large‑scale data easily consumable for intelligent systems.

Build datasets and derived aggregates supporting ML workflows and experimentation. Develop approximate analytical products using techniques such as sketches, probabilistic aggregation, and frequency estimation. Enable AI‑driven access to data through APIs, semantic retrieval, workflows, and emerging product experiences.

Help establish scalable interfaces between data products and ML/AI systems. Reconciliation and discrepancy management. Capacity and performance planning. Incident response and continuous improvement. Success is measured not simply by pipelines delivered, but by the reliability, adoption, usability, and business impact of the products built on top of them .

Technical Experience

Strong experience building and operating large‑scale distributed or data‑intensive systems . Strong understanding of data processing, distributed systems, APIs, and production system design.

Experience building backend services and APIs using languages such as Go, Java, Python, or similar. Strong understanding of data modeling, aggregation, partitioning, schema evolution, data correctness, and distributed processing.

Experience building reusable platforms, frameworks, APIs,



or abstractions rather than primarily one‑off pipelines.

Experience with large‑scale analytics, advertising technology, experimentation systems, ML infrastructure, customer‑facing data products, or data integration platforms is a strong plus. Strong technical judgment and ability to lead architecture and system‑design discussions. Ability to mentor senior engineers and raise the technical bar across a team.

Demonstrated ability to balance delivery, technical debt, reliability, and longer‑term architectural investments. Ability to translate ambiguous business problems into clear technical direction. Data Products owns the layer that transforms foundational data capabilities into reusable business and customer experiences: Real‑time data products Customer and partner integrations External data delivery Business‑oriented transformations and semantic layers Product‑level correctness, reconciliation, SLAs, and adoption The team partners closely with Data Platform and Exchange/Data Systems teams that provide foundational capabilities including storage, query infrastructure, catalogs, ingestion frameworks, Kafka, Flink, workflow orchestration, and shared observability.

A successful leader will help evolve Data Products from delivering individual datasets and reporting capabilities into an engineering organization that provides reusable, self‑service, real‑time, and API‑driven data products .

You will help us: Dramatically reduce the time required to launch new data products. Make real‑time and historical data accessible through consistent interfaces. Reduce coupling between product experiences and individual storage or BI technologies.

Enable customers, applications, operational systems, and ML workloads to consume data through well‑defined products. Create engineering capacity by automating repetitive workflows. Unlock current value from Index's data across reporting, optimization, experimentation, integrations, and AI/ML.

Comprehensive health, dental, and vision plans for you and your dependents Paid time off, health days, and personal obligation days plus versatile work schedules Competitive retirement matching plans Equity packages Generous parental leave available to birthing, non‑birthing, and adoptive parents Employee assistance program One day of volunteer time off per year and a donation‑matching program Monthly town halls and regular community‑led team events We celebrate diversity of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status. Additionally, we realize that diversity is deeper than any status or classification—diversity is the human experience. Accessibility for applicants with disabilities Index Exchange welcomes and encourages individuals with disabilities to apply to work with us.

Our corporate headquarters are in Toronto, with major offices in New York, Montreal, Kitchener, London, San Francisco, and many other global cities. AI Disclaimer Automated tools including artificial intelligence may be used to assist in screening and assessing applicants for this role.

📌 Engineering Lead Manager, Data Products (Toronto)
🏢 Index Exchange
📍 Toronto