Data Engineer, Business Intelligence at Rapid7
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.
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.
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 securityQualifications 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