Staff Data Engineer

Summary

Join Hypersonix.ai, a company disrupting the e-commerce space with AI and ML, as a Data Engineer. You will build and maintain optimal data pipeline architecture, assemble large datasets, and identify process improvements. Responsibilities include building data infrastructure using SQL and AWS technologies, running ad-hoc analysis, and working with cross-functional teams. You will also ensure data security across multiple data centers. The ideal candidate has 8+ years of experience, a graduate degree in Computer Science or Information Technology (or MCA), and strong SQL and big data experience. You will be instrumental in building and optimizing our product into an innovative industry leader.

Requirements

• 4 Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• A successful history of manipulating, processing and extracting value from large disconnected datasets
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
• Experience supporting and working with cross-functional teams in a dynamic environment
• We are looking for a candidate with 8+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Information Technology or completed MCA

Responsibilities

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements, should write complex queries in optimized way
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies
• Run ad-hoc analysis utilizing the data pipeline to provide actionable insights
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions
• Work with analytics and data scientist team members and assist them in building and optimizing our product into an innovative industry leader