The posting
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.
We’re a proud industry pioneer with over 20 years of experience accelerating the ad technology evolution. Our proprietary tech is trusted by some of the world’s largest brands and media owners and plays a crucial role in keeping the internet open, accessible, and largely free.
We process more than 550 billion real-time auctions every day (in comparison, Google processes 8.5 billion searches per day) with ultra-low latency. Our platform is vertically integrated from servers to networks and runs primarily on our own metal and cloud infrastructure. This end-to-end infrastructure is designed to provide both stability and agility, enabling us to adapt quickly as the market evolves.
At the core of it all is our engineering-first culture. Our engineers tackle internet-scale problems across tight-knit, global teams. 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. We move fast, build thoughtfully, and stay grounded in our core values.
About the role:
We are hiring a Staff Data Engineer to build and evolve the data processing and pipeline layer that powers reporting, billing systems, and real-time data streams at Index Exchange.
This role focuses on designing and operating large-scale batch and streaming data pipelines, enabling reliable, scalable, and efficient data transformation across the platform.
You will work on systems that transform raw, high-volume event data into clean, queryable, and production-grade datasets.
You will work on high-scale data systems that: Process billions of events per day across distributed pipelines Power core data platform supporting consumers as (reporting, billing, MLO teams) Operate across batch (Spark) and streaming (Kafka / Flink) architectures Require careful balancing of:data correctness processing efficiency latency vs cost trade-offs
You will solve problems such as: Designing pipelines that scale without exploding compute costs Managing data correctness at scale (deduplication, late data, joins) Building systems that support both:historical backfills near real-time updates
Evolving pipelines from centralized processing (Hadoop) toward more distributed and efficient patterns Streaming pipelines and Streaming DWs.
What we’re looking for: Strong experience in data engineering at scale Deep expertise in:Distributed Data Processing frameworks SQL and data modeling Leading Projects end to end
Experience with:Airflow or workflow orchestration Kafka or streaming systems Managing kubernetes
Strong understanding of:distributed data processing data modeling (large-scale datasets) performance optimization
Ability to:own pipelines end-to-end debug complex data issues work in high-scale, evolving environments
Staff-Level Expectations Define data processing standards and patterns across teams Lead large-scale pipeline and platform initiatives Influence data architecture and modeling decisions Drive improvements across:reliability cost efficiency scalability
Here’s what you’ll be doing:
Data Pipelines (Batch + Streaming) Design and operate pipelines using:Spark, Flink etc. Kafka / Flink (streaming)
Transform raw event data into:cleaned datasets (silver layer) business-ready datasets (gold / reporting tables)
Core Data Models & Datasets Build and maintain canonical datasets (aggregated datasets, reporting tables) Define data contracts and ensure consistency across pipelines Support evolving use cases:reporting billing ML / experimentation
Workflow Orchestration Build and maintain Airflow DAGs for:pipeline scheduling dependency management backfills
Improve reliability and observability of workflows
Data Processing Optimization Optimize pipelines for:performance (runtime, throughput) cost (compute efficiency) scalability (data growth)
Improve:partitioning strategies data layout job execution patterns
Streaming & Near Real-Time Pipelines Build pipelines that support:incremental updates streaming transformations aggregation at scale
Contribute to evolving patterns such as:edge aggregation streaming → batch convergence real-time data availability
Platform & System Design Responsibilities Define and evolve data processing patterns:batch vs streaming aggregation strategies incremental vs full recompute
Work across:Spark (core processing) Kafka (transport) Flink (streaming compute) storage systems (Hadoop / Ceph) Kubernetes
Contribute to:data platform architecture decisions pipeline standardization reusable data processing frameworks
Influence trade-offs:latency vs cost correctness vs performance compute vs storage
You will work closely with: Data Products ML and experimentation teams Infrastructure and on-prem systems
Here's What You Need: Bachelor/ Master’s Degree in Computer Science or Engineering related fields 8+ years of experience as a Software Engineer in enterprise grade, large scale distributed software product development 3+ years of work experience designing and building high performance data pipelines and applications using Hadoop/Ceph, Spark/Flink, Hive, Presto/Trino, Kafka, StarRocks/Vertica, Airflow, Kubernetes or other similar technologies Deep understanding of design principles of large scale distributed systems and familiar with mainstream big data related technologies and distributed frameworks Strong leadership, mentorship, and communication skills, with experience collaborating in a globally distributed, culturally diverse team Knowledge of data modeling, data warehousing, streaming data processing, and business intelligence reporting tools Experience working in Agile methodologies with continuous integration and delivery as CI/CD Experience working with containerization, and virtualization tools such as Kubernetes and Docker
Why You’ll Love Working Here: Comprehensive health, dental, and vision plans for you and your dependents Paid time off, health days, and personal obligation days plus flexible work schedules Competitive retirement matching plans Equity packages Generous parental leave available to birthing, non-birthing, and adoptive parents Annual well-being allowance plus fitness discounts and group wellness activities Commuter benefits and discounts, where available Employee assistance program Mental health first aid program that provides an in-the-moment point of contact and reassurance One day of volunteer time off per year and a donation-matching program Bi-weekly town halls and regular community-led team events Multiple resources and programming to support continuous learning A workplace that supports a diverse, equitable, and inclusive environment – learn more here
Equal employment opportunity At Index Exchange, we believe that successful products are built by teams just as diverse as the audience who uses them. As such, we are committed to equal employment opportunities. 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. For those who show grit, passion, and humility—Index will welcome you.
Accessibility for applicants with disabilities Index Exchange welcomes and encourages individuals with disabilities to apply to work with us. If you require an accommodation, please share the details of your request and any information how we can assist you with the hiring recruiter when they contact you. Index Exchange will make reasonable efforts to ensure accommodation requests are met throughout the recruitment process.
Index Everywhere, Index Anywhere Our corporate headquarters are in Toronto, with major offices in New York, Montreal, Kitchener, London, San Francisco, and many other global cities. As a major global advertising exchange, we are committed to operating as a tightly knit global team and embracing and empowering talent wherever our colleagues may be.
AI Disclaimer: Automated tools including artificial intelligence may be used to assist in screening and assessing applicants for this role. All hiring decisions involve human review.
Vacancy Status: This posting is for an existing vacancy.
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