Principal Software Engineer – Data Systems & Algorithms
Indexed description
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.
- 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.
- 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 with predictable latency and high availability.
- Experience with SQL and NoSQL databases such as PostgreSQL, MySQL, Cassandra, DynamoDB, MongoDB, ClickHouse, or similar technologies.
- Hands-on experience designing high-performance backend services using Java, C++, Go, Rust, or similar systems programming languages.
- Experience optimizing large-scale systems through efficient data structures, memory management, concurrency, and distributed computing techniques.
- Experience building cloud-native, highly available, fault-tolerant applications on AWS, Azure, or GCP.
- Experience designing and optimizing high-throughput data pipelines, event-driven architectures, or streaming systems.
- Strong understanding of observability, benchmarking, capacity planning, and production performance analysis.
- Demonstrated ability to drive architecture decisions, influence technical strategy, and lead complex engineering initiatives across multiple teams.
- Excellent problem-solving skills with a passion for solving complex engineering challenges.
- Bachelor's or Master's degree in Computer Science or a related field from a reputed institution.
- Opportunity to lead large, high-impact projects for global Fortune 500 clients.
- Work in a high-growth startup environment with a flat, collegial culture.
- Best-in-class remuneration and benefits.
- A platform for personal and professional growth with ownership and autonomy.
- Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.
- Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.
- Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.
- Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.
- Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.
- Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.
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