Staff Data Engineer

Staff Data Engineer

Location: New York, NY (Hybrid)
Pay: $200k - $250k Base

Overview

This Staff Engineer role sits within a growing data engineering organisation supporting multiple product lines inside a modern digital media and analytics company. The position plays a critical role in shaping shared data architecture, enabling cross‑platform collaboration, and driving the company's AI and generative AI roadmap.
You'll act as a senior technical leader - influencing architectural direction, mentoring engineers, and remaining hands‑on with production systems - ensuring data platforms scale coherently as products and teams continue to integrate and evolve.

Responsibilities

• Design, own, and evolve shared data architecture across multiple product platforms
• Establish scalable patterns and standards for data modelling, pipelines, and observability
• Lead technical strategy for integrating data products across teams to enable cross‑platform insights
• Drive the AI and backend infrastructure roadmap, including pipelines supporting ML and LLM‑powered features
• Collaborate closely with product, engineering, and ML teams to translate business needs into durable architectural decisions
• Mentor data engineers, identify skill gaps, and raise the overall technical bar across the organisation
• Evaluate and prototype emerging AI and generative AI technologies for real‑world product use cases
• Contribute to engineering planning, roadmap prioritisation, and support for production systems

Must‑Have Qualifications

• 8+ years of experience in data engineering, data architecture, or a closely related field
• Proven experience designing and operating large‑scale data systems across complex, multi‑product environments
• Strong experience with cloud data warehouses (e.g. Snowflake, BigQuery, or equivalent)
• Hands‑on experience building batch and streaming data pipelines using tools such as Spark, Kafka, Airflow, or similar
• Demonstrated experience integrating AI / ML capabilities into production data systems, including LLMs or foundation models
• Strong Python proficiency and data architecture expertise
• Excellent communication skills with the ability to influence both technical and non‑technical stakeholders