Rapid7 is a leading provider of security data and analytics solutions that enable organizations to implement an active, analytics-driven approach to cyber security. We combine our extensive experience in security data and analytics and deep insight into attacker behaviors and techniques to make sense of the wealth of data available to organizations about their IT environments and users. Our solutions empower organizations to prevent attacks by providing visibility into vulnerabilities and to rapidly detect compromises, respond to breaches, and correct the underlying causes of attacks. Rapid7 is trusted by more than 9000 organizations across 125 countries, including 52% of the Fortune 100. To learn more about Rapid7 or get involved in our threat research, visit www.rapid7.com. 

Job Overview

Rapid7 is looking for a Data Engineer to design and implement data models, own the ETL process & influence data warehousing strategy. You’ll help us organize the data we have today, but you’ll also create processes and monitoring for data quality, data management and ensure that standardized data models & data tables can be trusted and widely used. You’ll work with modern data warehousing technologies such as Snowflake, Airflow, Docker, AWS, Fivetran and more. In this role you’ll be the champion of our data, working in tandem with BI & Analytics analysts and managers to assure that we have the right data at the right time to support our business needs. All of this in support of our “single source of truth” and continuing our progression up the analytics maturity curve towards pervasive predictive and prescriptive analytics.

The ideal candidate has not only hands-on experience preparing large-scale data sets but also demonstrated examples of translating business objectives and requirements into the data needed to support key analyses. You’ll collaborate with a creative, analytical and data-driven team to bring a single source of truth and self-service analytics to over 1600 employees.

Essential Responsibilities

Create and maintain optimal data pipeline architecture, and implement structures and process to assure efficiency, repeatability and standardization in the use of data within the BI team and Rapid7 as a whole

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python, and other languages.

Own the data pipelines that support standard views needed across the BI Team

Collaborate with the IT and Infrastructure teams on integration efforts between systems that impact data & Analytics

Lead the development of data delivery processes to enable self-service analytics across the enterprise

Assemble complex data sets that meet reporting and analytics requirements from business stakeholders

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Self-starter orientation, able to handle the prioritization of multiple project and tasks under time-bound deadlines

Able to look for opportunities proactively to improve the business, outside of the specific questions asked, and understand how to influence the organization to make needed changes

Develop protocols and manage the data governance process to promote data standards, data quality & data security

Qualifications and Skill Requirements

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

More than 1 year of experience with modern data warehouse (Snowflake, Redshift)

More than 1 year of experience with cloud services (AWS, Azure, GCP)

More than 2 years experience building data pipelines

Extremely Proficient in SQL; understanding of a version control system such as Git 

Proficiency in Python, R, Java or other scripting language

Extensive experience in data integration (ETL) tools such as Informatica, SSIS, Talend, Fivetran, or AWS Glue

Working knowledge and solid understanding of data architecture, data warehousing, and metadata management

Experience in using data analysis and visualization tools such as Domo, Tableau, Qlik, or Power BI

Track record of managing and improving complex processes and very strong organizational and problem-solving skills