- 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-term product delivery with investments in architecture, automation, reliability, and engineering velocity.
- 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.
- Own correctness, reconciliation, discrepancy management, freshness, and SLAs for product-facing datasets.
- Design systems that allow new datasets, metrics, dimensions, and capabilities to be introduced quickly and safely.
- Drive self-service patterns that reduce one-off engineering work and make data capabilities reusable across the organization.
- Build streaming-derived datasets and real-time operational data products.
- Design business-oriented transformations and aggregations over high-volume event streams.
- Define and operate freshness and availability guarantees for near-real-time products.
- 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.
- 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.
- Customer-facing reporting products.
- Embedded analytics.
- Operational dashboards and troubleshooting experiences.
- Analytical interfaces used by internal and external consumers.
- Architectures that separate data products and semantic definitions from individual visualization technologies.
- 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.
- Establish consistent contracts, observability, governance, and operational guarantees across integrations.
- Drive self-service consumption patterns for downstream applications, partners, operational systems, and ML consumers.
- 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.
- Reliability and SLA adherence.
- Observability and operational resiliency.
- Automated recovery and operational workflows.
- Dataset and API correctness.
- Reconciliation and discrepancy management.
- Capacity and performance planning.
- Release coordination and production readiness.
- Incident response and continuous improvement.
- 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 with technologies such as Kafka, Spark, Flink, Kubernetes, Airflow, or comparable systems.
- Experience building backend services and APIs using languages such as Go, Java, Python, or similar.
- Experience with both batch and streaming architectures and the trade-offs between them.
- Strong understanding of data modeling, aggregation, partitioning, schema evolution, data correctness, and distributed processing.
- Experience designing reliable systems with clear SLAs, observability, and operational ownership.
- Experience building reusable platforms, frameworks, APIs, or abstractions rather than primarily one-off pipelines.
- Experience leading engineers responsible for complex production systems.
- 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.
- Strong cross-functional leadership and ability to influence teams outside your direct organization.
- Ability to translate ambiguous business problems into clear technical direction.
- Strong written and verbal communication skills.
- Curated datasets and aggregations
- Real-time data products
- Domain and reporting APIs
- Analytical and reporting experiences
- Operational troubleshooting products
- Customer and partner integrations
- External data delivery
- Business-oriented transformations and semantic layers
- Product-level correctness, reconciliation, SLAs, and adoption
- Dramatically reduce the time required to launch new data products.
- Increase reuse through common frameworks and standardized patterns.
- Improve freshness, correctness, reliability, and observability.
- 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 new 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 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
- Monthly 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
Skills Required
- Experience building and operating large-scale distributed or data-intensive systems
- Strong understanding of data processing, distributed systems, APIs, and production system design
- Experience with Kafka, Spark, Flink, Kubernetes, Airflow, or comparable technologies
- Experience building backend services and APIs with Go, Java, Python, or similar languages
- Experience with batch and streaming architectures and their trade-offs
- Understanding of data modeling, aggregation, partitioning, schema evolution, data correctness, and distributed processing
- Experience designing reliable systems with SLAs, observability, and operational ownership
- Experience building reusable platforms, frameworks, APIs, or abstractions
- Experience leading engineers responsible for complex production systems
- Strong technical judgment and ability to lead architecture and system-design discussions
- Ability to mentor senior engineers and improve technical standards
- Ability to balance delivery, technical debt, reliability, and architectural investments
- Strong cross-functional leadership and ability to influence teams outside the direct organization
- Ability to translate ambiguous business problems into clear technical direction
- Strong written and verbal communication skills
- Experience with large-scale analytics, advertising technology, experimentation systems, ML infrastructure, customer-facing data products, or data integration platforms
Index Exchange Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Index Exchange and has not been reviewed or approved by Index Exchange.
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Affordable Benefits — Medical, dental, and vision coverage is described as fully paid for employees and often for dependents in the U.S., reducing out-of-pocket costs. While specifics vary by region, public materials consistently emphasize low-premium coverage.
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Parental & Family Support — Parental leave is positioned as generous and inclusive, with birthing parents able to take extended fully paid leave and structured return‑to‑work support. Coverage also extends to non‑birthing and adoptive parents, with fertility benefits highlighted.
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Leave & Time Off Breadth — Time off combines substantial PTO with additional health days and personal obligation days, expanding rest and recovery options. Volunteer time off and the ability to work from another location for part of the year further broaden flexibility around time away.
Index Exchange Insights
What We Do
Index Exchange is a global advertising supply-side platform enabling media owners to maximize the value of their content on any screen. As a trusted partner and ally, we connect leading experience makers with the world’s largest brands to ensure a quality experience for consumers. We’re a proud industry pioneer with over 20 years of experience accelerating the ad technology evolution. With our radically transparent business practices and dedication to total market efficiency, we’re committed to upholding the integrity of the programmatic ecosystem at large. Our global teams are dedicated to driving industry standards and building technology that delivers scale, efficiency, and long-term value for our customers and partners. In our workplace, we pride ourselves on fostering an environment of openness where everyone feels connected and supported - a place where you can be your best inside or outside of work.
Why Work With Us
When you join Index Exchange, you’ll be working at an engineering-first company. Our foundation is our technology platform and all of the Indexers who come together to improve, extend, and reinvent it. We invest heavily in building an organization that’s committed to DEI&B, our core values, and our vision of total market efficiency.








