This position is in a functional area of financial analytics, policy operations, such as renewals and related insurance analytics.
The position is in a area of financial analytics, policy operations, such as renewals and related insurance analytics.
Insurance is a plus, but not required. The role is focused on building out pipelines in AWS with glue as the ETL.
Insurance is a plus, but not required.
The position is focused on building out pipelines in AWS, glue for ETL, python is highly desired, and Talend is a plus.
Everything will be housed in snowflake (required). They have already completed the proof of concept, and the initiating is emerging and underway.
The environment consists of Qlik Sense, some SSIS, old VBA, legacy, and MicroStrategy which will be used more and more. Experience on some of the BI Tools needed to understand how data pipelines will be consumed.
This person should be a data engineer that is familiar handling IaaS (infrastructure as a service) to information delivery and be able to coach and mentor others, as well as share and exchange expertise across the team.
Doing the transformation is the core skill and sharing their knowledge is highly important.
This is considered a full stack data engineer with over 70% of the work being designing/ creating cloud-based data pipelines and analytics
Questions asked during the interview will include how did you build out the pipeline? How did you maintain the pipeline?
What were the technical requirements to provide reliable data?
What was your contribution to the team?
What best practices are you familiar with?
In glue and python?
The team is made up of nine engineers, some full-time, some offshore, plus a scrum, master, a team lead, and a TPO
The hiring manager will only consider the last six years of skills, beyond that too old to be a factor as a knowledgeable skill.
Position is based on East Coast typical hours, 9 to 5, but anywhere in the 7:30 AM to 5:30 PM EST is acceptable.