Data Engineer

Strong proficiency in programming languages commonly used in data engineering, such as Python, SQL
Strong background in Data warehousing concepts and schema design
Understanding of popular code development approaches
Experience working with AWS services (Lambda, S3, Glue, Aurora, Dynamo)
Build processes supporting data transformation, data structures, metadata, dependency and workload management
Strong problem-solving skills and the ability to troubleshoot complex data-related issues with a prime focus on data quality and management
Excellent communication skills to collaborate with technical and non-technical stakeholders, laser focus on the impact, curiosity, team player

Provide data to the company’s analysts and decision-makers by supporting and developing massive data pipelines
Design efficient and scalable data pipelines for collecting, transforming, and loading data from various sources
Optimize data storage solutions while implementing strategies for query performance, cost and scalability
Plan and support identification of physical implementation requirements, including normalization/dimensional techniques and referential integrity
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Collaboration with analysts, data scientists, and business teams to recommend and improve data infrastructure
PST Hours and On-Call