Senior Software Engineer - Data Platform

About This Role

Jane Isis is seeking a Senior Software Engineer to join Project Labradoor, our ambitious initiative to revolutionize enterprise data management. This stealth project aims to solve one of the most persistent challenges in modern organizations: the fragmentation of valuable data across siloed systems, formats, and domains. You’ll be at the forefront of developing technology that creates a unified semantic layer across all enterprise data, enabling unprecedented insights and capabilities.

The Vision: Breaking Down Data Silos

Modern enterprises struggle with data trapped in isolated systems—ERP databases that don’t communicate with IoT sensors, unstructured documents disconnected from transactional records, and machine-generated logs isolated from business analytics. Project Labradoor addresses this challenge by creating a revolutionary data unification platform that:

• Digital Twin Creation: Generates virtual representations of all data entities, whether they originate from physical sensors, business applications, or unstructured content
• Semantic Ontology Development: Automatically constructs domain-specific knowledge graphs that capture the relationships, hierarchies, and business rules governing data entities
• Intelligent Data Linking: Employs advanced entity resolution and relationship inference to connect previously isolated data points across systems
• Unified Access Layer: Provides a single, coherent interface to query and interact with all enterprise data, regardless of its original source or format

Technical Challenges You’ll Solve

This role demands solving complex distributed systems challenges at the intersection of data engineering, knowledge representation, and high-performance computing:

System Architecture: Design distributed systems capable of ingesting millions of events per second while maintaining ACID guarantees for critical operations. Build polyglot persistence layers that optimize storage and retrieval for different data characteristics—time-series data in columnar stores, relationships in graph databases, and documents in search indices.

Performance Engineering: Implement lock-free data structures and zero-copy techniques in C++ and Rust for ultra-low latency data processing. Optimize memory layouts for cache efficiency and SIMD vectorization. Build custom allocators and memory pools to minimize garbage collection overhead in high-throughput scenarios.

Semantic Intelligence: Develop ontology inference engines that automatically discover conceptual models from raw data. Implement description logic reasoners for automated classification and consistency checking. Build SPARQL query processors that execute complex semantic queries across distributed knowledge graphs.

Language Diversity: Leverage each language’s strengths—Golang for concurrent microservices and API development, Rust for memory-safe systems programming, C++ for performance-critical components, and Python for ML pipelines and rapid prototyping.

Your Impact

Your work will fundamentally transform how organizations leverage their data assets:

• Accelerate AI/ML Adoption: Enable data scientists to access all relevant data through a unified semantic layer, reducing feature engineering time from months to days
• Enable Real-time Intelligence: Power applications that combine streaming IoT data with historical records and unstructured content for immediate insights
• Reduce Integration Costs: Eliminate the need for point-to-point integrations by providing a universal data access layer
• Unlock Hidden Value: Discover previously unknown relationships and patterns by connecting isolated data silos
• Democratize Data Access: Enable business users to query complex data relationships using intuitive semantic models

The Technology Stack

You’ll work with cutting-edge technologies across the entire data platform spectrum:

• Languages: Golang (microservices, APIs), Rust (core engine, performance-critical paths), C++ (query optimization, memory management), Python (ML pipelines, orchestration)
• Data Stores: Graph databases, time-series databases, vector databases, object stores, streaming platforms
• Frameworks: Apache Arrow for columnar processing, gRPC for service communication, WebAssembly for portable compute
• Infrastructure: Kubernetes for orchestration, service mesh for microservice communication, observability platforms for monitoring

Team & Culture

You’ll join a small, elite team of engineers who’ve built systems at companies like Google, Amazon, and Palantir. Our team includes experts in distributed systems, database internals, semantic web technologies, and machine learning. We value deep technical expertise, intellectual curiosity, and the ability to tackle ambiguous problems with creative solutions.

Growth Opportunities

This role offers unique career growth potential. As an early member of Project Labradoor, you’ll have the opportunity to shape the technical direction of a platform that could redefine enterprise data management. Successful delivery could lead to technical leadership roles, patent authorship, and the chance to present at major conferences as we bring this technology to market.

Why This Role Matters

Data silos cost enterprises billions in missed opportunities and inefficiencies. By joining Project Labradoor, you’ll help build the foundational technology that enables organizations to finally realize the full value of their data assets. This isn’t just another data platform—it’s a fundamental reimagining of how enterprises understand and interact with their information.

Application Process

Ready to break down data silos and build the future of enterprise data platforms? Submit your resume, GitHub profile, and a brief description of the most challenging distributed systems problem you’ve solved. We’re particularly interested in examples demonstrating your expertise across multiple programming languages and your ability to design systems that balance performance, scalability, and maintainability.