Data Privacy Engineer
Ibotta is looking for a Data Privacy Engineer to join our innovative team and contribute to our mission to Make Every Purchase Rewarding. Reporting to the Data Privacy Manager within Ibotta’s Risk Management team, the Privacy Engineer will help design and implement solutions to automate Ibotta’s privacy compliance obligations [such as data discovery and classification, data subject access rights (DSARs), data mapping and lifecycle management, among other privacy-by-design practices]. This individual will also provide reporting and analytics in support of Ibotta’s privacy program, and will work cross-functionally to identify and help mitigate potential privacy risks. Additionally, as a Data Privacy Engineer, you will have the unique, challenging, and rewarding opportunity to have a material impact on the company’s operations. By doing this, not only will you be able to advance your technical skills, but your organizational and leadership skills as well by contributing to the creation of best practices for the team and company.
This position is located in Denver, Colorado as a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Candidates must live in the United States.
What you will be doing:
Analyze large and novel datasets to extract actionable insights to inform business decisions and understand consumer behavior
Provide customized views of large and complex datasets to support data analysis and business decision-making
Contribute to creating best practices for the team
Analyze, design, program, debug, document, and maintain software enhancements and integrations to Ibotta-built and third party technologies in support of Ibotta’s DSAR, data mapping, data lifecycle, and other risk management and privacy-by-design efforts
Support the implementation and maintenance of privacy-by-design practices
Prepare privacy training, communication and awareness materials. Train internal teams on applicable privacy materials and initiatives
Help automate and manage Privacy Impact Assessments (PIA) and Legitimate Interest Assessments
Work with internal teams on documenting and maintaining a personal data inventory and Ibotta’s registry of processing activities
Monitor internal compliance against privacy policies and standards by conducting internal audits;
Identify potential areas of privacy risk and compliance vulnerability; develop/implement corrective action plans for resolution of problematic issues, and provide general guidance on how to avoid and remediate similar situations in the future;
Provide assistance to external and/or internal auditors in compliance review
Assist with response to suspected privacy incidents and breaches
Perform ad-hoc analysis to generate new privacy insights, and key metrics
Embrace and uphold Ibotta’s Core Values of Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere
What we are looking for:
2-3+ experience in a Software as a Service (SaaS) organization
Bachelor’s degree in Computer Science, Engineering, Analytics or a related field required
Familiarity with Amazon’s AWS infrastructure, cloud analytics, and SDLC best practices
Experience with ruby, php, python, java and/or modern data analysis tools (sql, r, splunk); and ability to fetch and transform large-scale datasets using a language like SQL or python for analyses
Ability to build concise and compelling data visualizations with modern data visualization tools (Looker, Mode, Tableau, Imply, etc.) preferred
Basic knowledge of US and International data protection regulations and privacy frameworks (e.g. OECD, US-EU Privacy Shield, PIPEDA, ePrivacy directive, and GDPR, CCPA/CPRA and other state privacy regulations)
High standards, impeccable integrity, unquestionable good judgment
Exceptional written and verbal communication skills, able to convey complex concepts to technical and non-technical stakeholders
Adapt to rapidly changing business processes and work efficiently under tight deadlines
Basic inferential statistics knowledge (for example: estimating a population mean from its sample, power analysis, basic knowledge of statistical tests to compare groups) preferred but not required
Experience partnering with a cross-functional group of engineers, operations, product, and leadership teams to achieve a common goal
Curiosity and the commitment to continually ask questions of our data and business
Ability to translate ambiguous business questions into structured data problems