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.
Apply architecture and system design theories and principles, perform complex work in research, design and development of new or existing products, tools and processes required for the operation, maintenance and testing of products.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS Azure ‘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.
Embed DevOps processes in delivery – ensure usability is front of mind in Tech Product development.
Keep our data separated and secure across national boundaries through multiple data centers and Azure platforms.
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.
Degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
At least 5 years of relevant experiences in a Data Engineer role. Experience using the following software/tools:
Experience with big data tools: Hadoop, Hive, Kafka, ELK (ECE), etc.
Experience with relational SQL and NoSQL databases such as MSSQL, Postgres, Cassandra, MongoDB, TimeScaleDB
Experience with mission-critical production development in following languages and frameworks a plus