Tech Lead, Data & Inference Engineer

The client is a venture-backed advertising technology startup transforming B2B marketing through identity resolution and data-driven audience targeting. The Tech Lead, Data & Inference Engineer will lead the design, development, and scaling of the end-to-end data platform, including batch and streaming pipelines, inference systems using large language models and retrieval augmented generation, reliability, architecture, and data quality. The role also involves mentoring engineers and establishing data-driven engineering practices across teams.

Responsibilities:

• Lead the design, development and scaling of an end to end data platform from ingestion to insights, ensuring that data is fast, reliable and ready for business use
• Build and maintain scalable batch and streaming pipelines, transforming diverse data sources and third party application programming interfaces into trusted and low latency systems
• Take full ownership of reliability, cost and service level objectives. This includes achieving ninety nine point nine percent uptime, maintaining minutes level latency and optimizing cost per terabyte. Conduct root cause analysis and provide long lasting solutions
• Operate inference pipelines that enhance and enrich data. This includes enrichment, scoring and quality assurance using large language models and retrieval augmented generation. Manage version control, caching and evaluation loops
• Work across teams to deliver data as a product through the creation of clear data contracts, ownership models, lifecycle processes and usage based decision making
• Guide architectural decisions across the data lake and the entire pipeline stack. Document lineage, trade offs and reversibility while making practical decisions on whether to build internally or buy externally
• Scale integration with application programming interfaces and internal services while ensuring data consistency, high data quality and support for both real time and batch oriented use cases
• Mentor engineers, review code and raise the overall technical standard across teams. Promote data driven best practices throughout the organization