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In this role, you will:
Build and maintain pipelines and infrastructure that ingest, analyze and store Rapid7's enterprise data using modern tools such as Snowflake, Airflow, dbt and AWS
Work closely with senior engineers to drive software lifecycle including hands-on development, testing, deployment, and documentation
Participate in scrum events include sprint planning, retrospectives and daily stand-ups
Productionize data through dev ops processes (such as CICD) using containerization tools such as ECS
Collaborate with stakeholders in product, business and IT to deliver high quality data products and assist with data-related technical issues
Support large scale projects including major implementations, process improvements, and cross-function data initiatives
The skills you’ll bring include:
BS in Computer Science, Analytics, Statistics, Informatics, Information Systems or
another quantitative field or equivalent experience; Should have broad knowledge of core computer science / software engineering concepts.
2-3 years of experience in a data-focused required; specifically as a Data Engineer or highly technical Analytics Engineer
SQL fluency and data warehousing understanding required; Working experience with a programming language is highly preferred
Working knowledge with modern data tools such as Snowflake, dbt, Airflow, and AWS
Capable of taking well-defined tasks and completing these tasks with minimal supervision
General understanding of the SDLC including modern dev ops tools, code reviews, testing, and planning
Strong work ethic, resiliency, persistence, and urgency; Data Engineering holds itself to a high standard so you’ll need to keep up!
Sharp business and interpersonal skills; Should be able to effectively communicate status and escalate blockers
Be a team-player! Data Engineering has a nice balance of independent vs codependent - One Moose!
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