Data Engineer
Evive people are game-changers.
Evive was founded by two people who wanted to challenge the status quo...and did. More than 11 years later, that spirit still defines our culture. The work we do is redefining how people use their employee benefits, with SaaS-based services that help people to improve their lives and Fortune 1000 enterprises to optimize their benefits investments. We strive every day for the ideal of #benefitslove. Are you one of us?
We’re looking for a thorough Data Engineer. Is it you?
The Data Engineer designs and builds the data pipelines that will enable faster and more accurate data-informed recommendations and decisions both inside and outside of the Evive platform. On a daily basis they design and build services to collect, compile, normalize, and analyze data assets coming from multiple sources internally and externally. The Data Engineer understands good API Design, Data Pipelining, and is diligent about Data Security.
Here's what a Data Engineer does at Evive (for people who like bullet lists):
Designing, developing, and maintaining data architecture: Responsible for creating the infrastructure and framework to support the storage, processing, and retrieval of data. This includes designing and maintaining databases, data warehouses, data pipelines, and other data management systems.
Building and maintaining data pipelines: Responsible for creating the software and tools necessary to move data from various sources to the target data storage systems. This includes designing and maintaining ETL (Extract, Transform, Load) pipelines, data integration solutions, and other tools to facilitate data movement.
Ensuring data quality and security: Data engineers must ensure that the data being used by the organization is accurate, consistent, and secure. This involves developing and implementing data quality controls, monitoring data for errors and inconsistencies, and implementing security protocols to protect sensitive data.
Collaborating with Data Scientists and Analysts: Data engineers work closely with Data Scientists and analysts to understand their data needs and develop solutions to meet those needs. This includes designing and implementing data models, building data visualization tools, and developing algorithms to process and analyze data.
Data Engineers must stay up to date with the latest trends and technologies in the data engineering field to ensure that the organization is using the most efficient and effective data management solutions
Knowledge, Education and Experience: