Senior Data Engineer, Business Intelligence

US - Remote

Location(s)

US - Remote, US - MA - Boston

Team(s)

Product & Engineering


Rapid7 (Nasdaq: RPD) is advancing security with visibility, analytics, and automation delivered through our Insight cloud. Our solutions simplify the complex, allowing security teams to work more effectively with IT and development to reduce vulnerabilities, monitor for malicious behavior, investigate and shut down attacks, and automate routine tasks. Over 9,300 customers rely on Rapid7 technology, services, and research to improve security outcomes and securely advance their organization. For more information, visit our website, check out our blog, or follow us on LinkedIn

The Opportunity 

Rapid7 seeks a Sr. Data Engineer to build and maintain data infrastructure within the Business Intelligence team's data platform. You will be responsible for deploying data pipelines and machine learning models in the cloud, implementing DevOps practices and developing data models within Snowflake. You will work closely with AWS, Snowflake and DevOps applications such as Github Actions, Terraform, Jenkins and more. In this role you will bridge the gap between a data engineer and a DevOps engineer by building monitoring systems, cloud applications and CI/CD pipelines that support the data engineering team's efforts. 

The ideal candidate has hands-on experience performing DevOps work in a cloud environment, and has worked closely with databases and data pipelines. It's critical that you are able to translate  business objectives into data required to support key analyses. You will collaborate with a creative, analytical and data-driven team to bring a single source of truth and self-service analytics to the entire company.

In the role you will: 

  • Transform Rapid7's Business Intelligence and Analytics data platform by applying DevOps best practices of automation, monitoring, CI/CD and configuration management

  • Build and maintain the applications that ingest, analyze and store Rapid7's enterprise data 

  • Mentor and provide guidance to peer data engineers based on your experiences and technical expertise

  • Productionize data and machine learning pipelines with docker containerization and clustering tools (ECS/Kubernetes) 

  • Develop effective monitoring and alerting systems to provide real-time visibility into the health of data infrastructure, cloud applications and data/machine learning pipelines 

  • Build an environment that enables data scientists to easily develop and productionize Python, R and Spark code on top of a Snowflake data warehouse

  • Automate existing code and processes using scripting, CI/CD, infrastructure-as-code and configuration management tools 

  • Perform data engineering projects within Snowflake such as developing data pipelines, data models and metadata management solutions

  • Collaborate with stakeholders in product, business and IT to deliver data products

  • Work closely with leadership to drive adoption of the latest DevOps and DataOps trends and technologies

  • Partner with the IT, Infrastructure and engineering teams on integration efforts between systems that impact data & Analytics

In return you will bring: 

  • 3+ years of experience with a major cloud provider (preferably AWS) including hands-on experience with code deployment in cloud environments using tools such as Docker, Kubernetes, EC2, Terraform

  • More than 3 years of experience working with a modern cloud data warehouse (preferably Snowflake) and SQL, plus 1+ years of experience with orchestration tools (preferably Airflow)

  • 3+ years of experience in at least one programming such as Python, Java, Scala etc. 

  • Experience as a leader within a data engineering team and ability to mentor teammates 

  • Strong written and verbal communication skills 

  • Highly collaborative in working teammates and stakeholders 

  • Experience with a CI/CD tool such as Github Actions and AWS Code Pipeline

  • Working knowledge of data architecture, data warehousing, and metadata management

  • BS or MS in Computer Science, Analytics, Statistics, Informatics, Information Systems or another quantitative field. or equivalent experience and certifications will be considered
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