Senior Staff Software Engineer - Data Delivery
S
StackAdaptAdtech
Location: Canada; United StatesFull-TimeStaff
Salary not disclosed
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Job Details
- Required Skills
- Backend DevelopmentKafkaGoRESTful APIsReportingRedshiftDistributed Systems
Requirements
- Broad technical leadership: Experience shaping technical direction across teams, domains, or large platform areas.
- Backend and data systems expertise: Deep experience building scalable services, distributed systems, data platforms, or data-intensive applications.
- Strategic system design: Strong judgment across APIs, data pipelines, databases, distributed systems, observability, reliability, and long-term architecture.
- Cross-functional influence: Ability to align engineering, product, data science, analytics, and business stakeholders around technical strategy.
- Platform thinking: Ability to design systems that create leverage for multiple teams and make future product development easier.
- Data quality mindset: Strong ability to reason about correctness, freshness, completeness, consistency, explainability, cost efficiency, and customer trust.
- Business and product judgment: Ability to connect technical investments to customer impact, product velocity, reliability, and long-term business value.
- Technical communication: Ability to explain complex technical trade-offs clearly to both technical and non-technical audiences.
- Mentorship: Experience developing senior engineers and raising engineering standards across a team or domain.
- Technical stack: Strong programming skills; experience with Golang and technologies such as Kafka, TiDB, Redshift, Vitess, Iceberg, StarRocks, or Trino is a plus.
- Domain experience: Experience in adtech, marketing technology, reporting, analytics, billing, attribution, forecasting, or high-volume event processing is a plus.
Responsibilities
- Technical strategy: Shape the long-term architecture and technical direction for Data Delivery and related Stats & Analytics systems.
- Cross-team leadership: Lead initiatives that span multiple teams, systems, and product areas, helping teams align on durable technical solutions.
- Platform enablement: Build and guide systems that make it easier to launch new reporting, measurement, forecasting, billing, export, and analytics capabilities.
- System design: Make high-impact technical decisions across APIs, data pipelines, data models, distributed systems, storage, serving layers, and operational patterns.
- Product partnership: Work with product, engineering, data science, analytics, and business leaders to translate company priorities into technical roadmaps.
- Technical quality: Identify systemic gaps in reliability, scalability, data quality, developer experience, and operational ownership, then drive improvements.
- Decision-making: Clarify trade-offs around correctness, latency, freshness, cost, migration complexity, maintainability, and long-term platform leverage.
- Technical mentorship: Coach and mentor engineers, including senior engineers, through architecture reviews, design discussions, and strategic technical guidance.
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