Data Engineer

Job Description: 10+years of focused hands-on AWS and Data Stack (EMR, Spark, Redshift, Athena, Glue, Serverless Lambda using Python, PostgreSQL/ Aurora/ RDS + DynamoDB, Kafka/ Kinesis) *Experience with Data Engineering – Ingestion, pipelines, cleansing, transformations, data lake, experience with batch and stream data processing" Candidate Profile: Must Have: Min. 6+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements. 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. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. 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. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems.