Principal Data Engineer/ Technical Lead

The Impact U will make:

We're seeking an experienced Principal Data Engineer/ Technical Lead who is passionate about implementation and capable of writing high-quality application code. In this role, your primary goal is to design and build the services, abstraction layers, and middleware that transform application data needs into specific, high-performance database operations and serve as a dynamic player-coach for our core data engineering squad. As a technical leader, you will directly impact system performance and latency issues that affect our enterprise customers while fostering an inclusive, high-performing engineering culture.

Key Responsibilities

• Act as a player-coach, providing technical direction, architectural guidance, and daily mentorship to a focused team of 3–5 engineers. Conduct thoughtful code reviews and foster professional growth within your squad.
• Design and implement sophisticated Data Access Layers (DAL) and custom ODMs to translate platform-generated, SQL-like queries into high-performance MongoDB BSON operations and aggregation pipelines.
• Build and maintain middleware that ensures Unqork’s core business logic remains storage-agnostic, enabling seamless modularity and flexibility across different data storage mechanisms.
• Architect and scale a multi-tenant, secure MongoDB ecosystem. Lead strategies for ensure high availability while performing deep-dive execution plan analysis (IXSCAN vs. COLLSCAN) to optimize query performance.
• Plan and architect hybrid data architectures to support operation, transactional and analytical schema and database systems.
• Use Node.js and JavaScript to build robust microservices (typically GraphQL) and internal libraries that integrate dynamic, metadata-driven data patterns into the Unqork no-code runtime.
• Design schemas and declarative models that allow non-technical users to build complex application logic without compromising data integrity or system performance.
• Architect real-time and batch data pipelines using Apache Kafka and Spark to facilitate data transformation and movement between relational and NoSQL systems.
• Partner with Platform and Backend engineers to standardize data interaction patterns, ensuring high-scale, API-driven performance across the e