What is Privacy Engineering and Why Its not as complicated as it sounds with Cat Easdon

PurePerformance

"Privacy engineering is the art of translating privacy laws and policies into code, figuring out how to make legal requirements such as ‘an individual must be able to request deletion of all their personal data’ a technical reality.", was the elegant explanation from Cat Easdon when asked about what she is doing in her day job.
If you want to learn more then tune in to this episode. Cat, Privacy Engineer at Dynatrace, shares her learnings about things such as: When the right time is to form your own privacy engineering team, why privacy means different things for different people and regulators and what privacy considerations we specifically have in the observability industry so that our users trust our services!
Links:
Cat's LinkedIn Profile: https://www.linkedin.com/in/easdon/
Publications from Cat: https://www.dynatrace.com/engineering/persons/catherine-easdon/
Blog on Managing Sensitive Data at Scale: https://www.dynatrace.com/news/blog/manage-sensitive-data-and-privacy-requirements-at-scale/
Semgrep for lightweight code scanning: https://github.com/semgrep/semgrep
The IAPP: https://iapp.org/
'Meeting your users' expectations' is formally described by the theory of contextual integrity: https://www.open.edu/openlearncreate/mod/page/view.php?id=214540
Facebook's $5 billion fine from the FTC: http://ftc.gov/news-events/news/press-releases/2019/07/ftc-imposes-5-billion-penalty-sweeping-new-privacy-restrictions-facebook
Fact-check: "The $5 billion penalty against Facebook is the largest ever imposed on any company for violating consumers’ privacy and almost 20 times greater than the largest privacy or data security penalty ever imposed worldwide. It is one of the largest penalties ever assessed by the U.S. government for any violation." I think that's still true; the largest fine under the GDPR was €1.2 billion (again for Facebook/Meta)