Principal Software Engineer – Data Systems & Algorithms

About Impact Analytics

Impact Analytics is an agentic-first AI software company transforming retail merchandising through cutting-edge AI, LLMs, and Generative AI technologies. As a fast-growing Series D company with deployments across five continents, it is building both industry-leading merchandising solutions and foundational AI agents that are redefining how retail decisions are made. It is one of the few India-born AI companies recognized globally by organizations like Fortune, Gartner, and the Inc. 5000.

For candidates looking to work on next-generation AI products with global scale and real-world impact, Impact Analytics is an exciting place to build your career. Here’s a link to our website: www.impactanalytics.co.

The impact that you will be making

Impact Analytics builds AI-powered, cloud-native products and platforms. As we solve increasingly complex data engineering and distributed systems challenges, we are looking for a Principal Engineer who has deep expertise in data storage, retrieval, advanced algorithms, and scalable data structures to architect the next generation of our platform.

What You'll Do

• Design and build highly scalable, low-latency backend systems capable of handling massive datasets.
• Architect storage and retrieval layers for structured, semi-structured, and unstructured data.
• Solve complex engineering problems involving advanced algorithms, indexing, search, caching, and distributed data systems.
• Drive technical strategy and architectural decisions for core platform components.
• Optimize system performance through efficient data structures, concurrency, memory management, and distributed computing techniques.
• Collaborate with AI/ML, Platform, and Product teams to build data-intensive applications.
• Mentor senior engineers and establish engineering best practices for scalability, reliability, and maintainability.
• Lead design reviews, technical discussions, and architectural governance across multiple teams.
• Continuously evaluate emerging technologies to improve platform performance and engineering productivity.
• Architect distributed data platforms that deliver predictable performance at billion-record scale and support mission-critical workloads.
• Design partitioning, sharding, replication, and data lifecycle strategies to ensure scalability, resiliency, and cost efficiency.
• Drive architecture for multi-region, highly available systems with strong disaster recovery and fault tolerance.
• Lead performance engineering initiatives across storage, compute, memory, and networking layers to optimize latency and throughput.
• Establish architectural standards for benchmarking, observability, capacity planning, and performance optimization.
• Evaluate and recommend database technologies, storage engines, and distributed computing frameworks based on evolving business needs.
• Drive architectural reviews for complex data-intensive systems and provide technical leadership on critical engineering decisions.

What Lands You In This Role

• 12–18+ years of experience architecting and building large-scale backend, distributed systems, or data platforms.
• Strong computer science fundamentals with deep knowledge of algorithms, data structures, complexity analysis, and system design.
• Expertise in designing systems for storing, indexing, querying, retrieving, and processing large-scale structured, semi-structured, and unstructured data.
• Deep understanding of database internals, including storage engines, query optimization, indexing strategies, transaction processing, concurrency control, and performance tuning.
• Strong understanding of distributed systems, including partitioning, sharding, replication, consistency models, fault tolerance, distributed caching, and messaging systems.
• Experience designing highly scalable storage and retrieval systems.