Qualify deals through collaboration with the Sales as a whole which may include selling partners.
Establish an effective working relationship with Sales and Services to assist in all stages of deal closure
Perform discovery in a customer SAS environment, determining which algorithms will convert out of the box and which will require manual adjustment
Help Services create Statements of Work (SOW) that summarizes discovery and captures the effort and scope needed to reliably deliver an SLC project
Analyze current customer SAS architecture and design an potential target migration proposal for SLC
Work with product management, support and engineering to new major, minor roadmap activity
Study and understand custom solutions of the clients and build a similar solution in SLC or use open-source technologies (R, Python) to achieve similar or better results
Attend customer meetings and be the face of Siemens DISW SLC
Travel is required to either meet directly with clients or as part of a selling team for presentation and demonstration. This is 25-35% time overall as-needed basis
Manage demands of Sales pipeline activity and triage your own time and getting help just ahead of need
Design and create SLC related demonstrations, Proofs-of-Concept (POC), and evaluations that clearly illustrate how to apply Dataiku to deliver the required customer value.
Work closely with Siemens services and other partners to ensure enablement at all stages of the sales cycle.

Requirements

7+ years’ experience in various facets of presales in enterprise selling
3-5 years experience directly with SAS environments
Seasoned in all facets of customers interaction and communication
Knowledge and experience of data architecture, data processing, database systems and analytics
Knowledge of the SQL language and other business analytics tools and languages
Experience administering SAS platforms like SAS Grid.
Knowledge of mainframes, AIX and Linux
Knowledge of SAS based mainframe reporting packages like MICS and MxG
Liaise with different teams - Engineering, Database, Support, Cloud, Testing, QA, Documentation.
Data science programming languages (R, Python).
Experience with Cloud Computing technologies like AWS/Azure/GCP/OCI and/or Docker/Kubernetes is desirable.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SASSQLRPythondata architecturedata processingdatabase systemsanalyticsCloud ComputingSAS Grid

Soft Skills

collaborationcommunicationcustomer interactionrelationship buildingtime managementpresentation skillsproblem-solvingteamworkadaptabilitycustomer service