Responsibilities:

• Create prototypes and proof-of-concepts for iterative development.
• Experience with NoSQL databases, such as DynamoDB, MongoDB, etc.
• Create and maintain optimal data pipeline architecture.
• 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.
• Evangelize a very high standard of quality, reliability, and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow.
• Build and enhance data pipeline architecture by designing and implementing data ingestion solutions.

Requirements:

• Experience with ETL, Data Modeling, and Data Architecture.
• Design, build, and operationalize large-scale enterprise data solutions and applications using one or more AWS data and analytics services in combination with 3rd parties - Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, and Glue.
• Experience with AWS cloud data lake for the development of real-time or near-real-time use cases.
• Experience with messaging systems such as Kafka/Kinesis for real-time data ingestion and processing Build data pipeline frameworks to automate high-volume and real-time data delivery.