Senior Data Engineer at Kenna Security
Senior Data Engineer
- ENGINEERING – DATA ENGINEERING
- FULL TIME
Kenna Security is revolutionizing cyber risk with a SaaS-based platform that uses data science to combine vulnerability data with exploit intelligence to measure risk, predict attacks and prioritize remediation. We are leading the way in helping enterprises reduce their risk while increasing their efficiency and preventing attacks. Kenna Security was recently named one of the top 10 hottest start-ups and named to the Inc. 500 fastest-growing companies list.
We’re looking for a Senior Data Engineer to jump into our data platform with an eye towards a well-tested, secure and performant product. If you’re comfortable in working within a highly autonomous, agile, and iterative software development process; Kenna might be the fit for you! This position is an opportunity for an engineer to join a growing engineering team and contribute to the maintenance, expansion, and scale of the Kenna data platform. Engineers are expected to take ownership of technical problems, craft solutions to complex problems, and craft code that meets our internal standards for maintainability and best practices. Our applications are widely used across the industry and your work will be used by millions of people every month.
There are a lot of security companies out there, but no one is doing what Kenna is doing: giving our customers the ability to measure their risk landscape and truly protect their environments from the ever-present threat of a breach. As a result, we’re seeing phenomenal growth as some of the top companies in the world flock to our platform. We have solid venture funding, an astonishing team who will support you to accomplish the impossible, and we even offer great benefits and stock options.
What are some of the interesting problems you’ll be working on:
- Work with an architect to design and own how data flows through our business, soup to nuts, working collaboratively across the company to partner with all departments.
- Manage an efficient data platform to support our products as well as a BI function using modern, low maintenance cloud technologies (AWS or GCP), as well as cleanly interfacing with our existing data science research technologies.
- Evolve a sophisticated data model to consume structured data from a growing set of source systems (scanners, VI feeds, etc).
- Author and maintain entity-relationship diagrams, data dictionaries, API specs, and data translation documentation at multiple levels of abstraction (conceptual, logical, physical) and across multiple data store technologies (relational, NoSQL).
- Implement solutions to proactively monitor data quality with traceability to source systems.
- Work with cross-functional product development teams on data modeling rules, standards, and best practices, embedding when needed.
What does it take to work at Kenna:
- BS in Computer Science, Computer Engineering or related industry experience.
- You have a product-oriented, cloud-first perspective on data.
- You have strong experience with distributed compute along with ETL/ELT and BI architectures using public cloud technologies, concepts and frameworks, especially around streaming of big data.
- Strong, proven data modeling experience at large scale.
- 5+ years experience with large-scale, distributed data pipelines, as well as data management, modeling, and storage
- 3+ years building large scale data processing and analytical systems in GCP or AWS with Dataproc, Airflow, BigQuery, Dataflow, Kafka, etc.
At Kenna you can enjoy the following:
- Competitive compensation package
- Medical, Dental, Vision & Disability Insurance
- Wellness Programs
- Pet Insurance
- Retirement Planning
- Company Equity
- Generous Paid Parental Leave
- Work From Home Setup
- Employee Referral Program
- Discretionary Time Off
- Friendly & Casual Environment
- Work/Life Balance
- Professional Development Program
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex or national origin.
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