Principal Engineer - Analytics

LogiNext is seeking a passionate Principle Engineer - Analytics to develop data products that extract valuable business insights for efficiency and enhanced customer experience. As a Principle Engineer, you will be responsible for managing, processing, and analyzing large volumes of raw information within scalable databases. Your role will also involve crafting unique data structures and designing algorithms for a new range of products. To excel in this role, you must possess critical thinking and problem-solving abilities. You should have a strong background in software development, advanced algorithms, and the capability to handle extensive data sets. Familiarity with statistics and machine learning algorithms is advantageous. Exposure to cloud environments, continuous integration, and agile scrum processes is also preferred. Responsibilities: - Lead projects as both a principal investigator and project manager, ensuring timely delivery of project requirements - Develop software that integrates data-driven intelligence into products with Big Data backends - Conduct exploratory data analysis to create efficient data structures and algorithms based on project needs - Implement advanced algorithm development, possibly incorporating machine learning models and pipelines - Manage data in large-scale data stores (e.g., NoSQL DBs, time series DBs, Geospatial DBs) - Establish metrics and evaluate algorithms to enhance accuracy and recall rates - Optimize data access and utilization through indexing, clustering, and other techniques - Collaborate closely with engineering and product development teams Requirements: - Masters or Bachelors degree in Engineering (Computer Science, Information Technology, Information Systems) from a top-tier institution, or a higher degree in Statistics, Mathematics with hands-on software development experience - 8 to 10 years of product development experience, including algorithmic work - 5+ years of experience working with large datasets or performing large-scale quantitative analysis - Proficiency in SaaS products and services - Strong problem-solving skills with algorithms - Ability to mentor and manage teams, meeting project deadlines - Proficient in Python programming - Understanding of software architecture and design principles - Project management experience, preferably in an Agile environment - Familiarity with data processing, analytics, and visualization tools in Python (e.g., pandas, matplotlib, Scipy) - Proficiency in SQL and querying NoSQL databases (e.g., Mongo, Casandra, Redis) - Knowledge of large database management practices like indexing, sharding, and caching - Exposure to Big Data technologies such as Hadoop, Yarn, Redshift, Spark, Kafka, Pig/Hive - Understanding of machine learning algorithms - Knowledge of geospatial data stores, experience with PostGIS is a plus - Desirable experience with data visualization tools Note: This Job Description is subject to change as per the company's requirements and policies.,