Senior Data Engineer

Role overview

This role architects and builds the foundational data pipeline infrastructure that powers a decentralized Data Mesh strategy, supporting the migration of a data ecosystem from legacy on-prem systems to a modern cloud data platform. The position also leads a small data engineering team, mentors analysts across the business, and ensures the data platform is structured to support next-generation, natural-language self-service analytics and AI features.

Responsibilities

- Design, build, and maintain scalable data pipelines supporting batch, real-time streaming, and event-driven movement from on-prem and cloud sources. - Serve as the core developer for the Snowflake data platform, ensuring optimal performance, modeling, and storage structures. - Architect transformation pipelines and semantic layers that deliver high-quality inputs to AI features and natural-language data interfaces. - Establish reference architectures, standard templates, and CI/CD best practices that enable decentralized line-of-business teams to build safely. - Provide direct management and career mentorship to data engineers, while coaching self-taught analysts on engineering practices and governance. - Drive the adoption of dbt for data transformation and explore integration of cloud data tools across AWS and Azure to optimize data flow.

Requirements

- 5–7 years of dedicated data engineering experience with a proven track record of building production-grade data pipelines. - Advanced, hands-on experience with Snowflake architecture, performance tuning, and data sharing. - Proven experience moving data across hybrid environments using batch, streaming, and event-driven patterns. - Experience building or maintaining semantic layers and structuring data for consumption by AI, LLM, or natural language search features. - Strong Python skills in cloud environments and strong SQL capabilities. - Collaborative, coaching mindset with a passion for teaching, governance, and raising the technical bar across teams.

Nice to have

- Exposure to dbt, Azure Data Factory, and AWS data ecosystem tooling. - Experience working directly with clients and cross-functional engineering teams on AI adoption initiatives.

Benefits and work setup

- Opportunity to work with leading financial institutions and other clients on meaningful AI adoption projects. - Equal opportunity employer; H1B visa sponsorship is not provided.