While the role is broadly understood as “Sales Engineer,” a poly blue suit and white shirt (women’s or men’s) are neither required nor recommended to excel in our version of the role.
We hope you are reading this because you are already an accomplished professional but something is missing in your career. Let’s get several big “ifs” out of the way so you can decide if Aginity might be the answer to your question: “Where do I next take my career”?
If you can shape-shift with execs and technologists and have each constituent think “Hmm…this person is just like ME and gets MY issues”…
If you have great “client appeal” because of your technical knowledge and interpersonal skill…
If you have an excellent academic and professional experience pedigree…
If you are inquisitive, self-demanding, and ambitious…
…then we should talk. Fear not for you will not be stuffed into a New York City pigeon hole with no means of escape. This role can be as big as you make it.
The Sales Engineer moves deftly between the business and technical with skills in analytics, database and data warehousing solution architecture, business intelligence, business analysis, and technical presentation, supported by a superior client-facing presence.
- Understand our prospect, the business they are in, their criterion for success, and work with our Account Executives to design and perform demonstrations for “Amp”, our Analytic Management Platform software.
- Execute technical, onsite customer proof-of-concepts to demonstrate Amp in our Prospects’ production environment.
- Prepare sales presentation and education decks.
- Collaborate with Sales team to share account insight and develop strategies for increasing account penetration and revenues.
- Relay to Product Management and Product Engineering field-level feedback on our software…the good, the bad, the ugly, so that all parts of Aginity improve.
- Design high-level architecture of big data analytic solutions that comprise aspects of data warehousing, data engineering, business intelligence, operational analytics and predictive analytics needs.
- Assist in the sizing, scoping, estimation and planning of implementation services for the post-sales deployment of our software.
- Provide continuity into post-sales by working with the Customer Success organization to ensure the pre-sales vision carries into post-sales value for the customer.
- Develop competitive analysis reports, SWOT assessments and competitive messaging on other emerging players in the nascent analytics management category.
- Work on a distributed team and collaborate to deliver compelling demos under tight time constraints.
- Learn new vertical markets so that you can incorporate their needs into your SE-specific sales toolkit
- Bachelor degree in something like software/computer engineering or close equivalent.
- Broad and deep experience with Netezza, Teradata, or other MPP data warehousing platforms and solutions for very large databases.
- Proven experience within the expanding Hadoop and open-source big data ecosystem with the highest priority on Spark and Hive
- Conceptual and logical data modeling or data architecture
- Strong to very-strong SQL and query optimization coding skills.
- Understanding of the Data Science or advanced modeling lifecycle from Data -> Prototyping -> Model Development -> Deployment.
- Basic understanding of statistics, modeling and common algorithms or techniques.
- Experience selling enterprise software solutions
- Experience architecting enterprise data solutions with multiple technology components including data storage, processing and business application integration.
- Experience with data analysis, profiling and source-to-target mapping in traditional data warehouse environments. Business and Data analysis… creative visualization and communication of insights to business users. Excellent technical and relationship building skills in working with prospects, customers, partners and sales to ensure Aginity delivers optimum solutions to our customers.
- Project management experience in some form (e.g team-lead or team management)
Hands on experience with at least two of the below categories of software:
- Developing cloud data solutions in Google, IBM, MSFT or AMZN cloud.
- Marketing execution software including such technologies as Unica (IBM Campaign), Aprimo, SAS Marketing Automation, etc.
- Data Science or Statistical Modeling languages and applications such as R, SAS, SPSS, Python, Scala, etc.
- Experience developing with Business Intelligence or Data Visualization software such as Cognos, Business Objects, AtScale, Qlik, Tableau
- Cloud analytics solutions such as H2O, DOMO, Birst, IBM Watson Analytics
- Data Prep or Data “Wrangling” tools such as Alteryx, Datameer, Paxata
- Online ad-tech ecosystem (DMP, DSP, etc.)
- Familiarity with Linux/Unix. You can find your way around a file system, manipulate files and prep data for integration.
- Domain expertise desired, but not required: Financial Services, especially risk modeling
- Direct marketing, market segmentation, customer/consumer analytics, email marketing, and campaign management using advanced behavioral data analytics.
- Loyalty analytics (any industry)