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. What makes Impact Analytics unique is its combination of deep retail domain expertise, strong innovation culture, and global presence. 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 What lands you in this role:

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.