Solutions Engineer
Sorry, this job was removed at 3:31 p.m. (EST) on Wednesday, September 18, 2019
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Apply if you are…
- Excited about implementing cloud-based SaaS solutions
- Energized about working at a fast-paced start-up with high levels of uncertainty and change
- Psyched to work with a talented team that is moving the needle on the most pressing challenges in US healthcare
- Deeply hands-on and excited to work with cutting-edge cloud computing technology in a dynamic agile environment
- Open-minded and a strong communicator who knows how to interact with Customer teams as well as with Product and Engineering teams
You should expect to….
- Be the technical customer advocate within Abacus. To aid your customers, you will work closely with Product and Engineering teams to ensure implementation backlogs are synced up appropriately with the product delivery roadmaps. You will rally the entire organization as you seek out and create scalable solutions for your customer’s needs.
- Synthesize complex data/information and lead large technical implementations. Ability to matrix manage/organize Abacus, Client and Vendor teams in order to get work done quickly.
- Build relationships with and partner with technical and non-technical stakeholders.
- Work directly with our clients and implementation teams to manage overall timelines and communicate progress.
- Maintain awareness of internal roadmap and new product features to evangelize with customers and their feedback to Abacus product management and engineering groups.
- Continuously learn and update skills in the data integration and data management space.
- Collaborate and contribute to engineering effective demos.
Terrific if you have…
- Prior experience in a solutions engineering role, with a record of top performance in the B2B SAAS space for enterprise accounts
- A firm understanding of enterprise data integration and data management methodologies and architectures
- Expertise in cloud computing and big data technologies related to master data management, data warehouse, data virtualization, data quality, data reconciliation and data governance design patterns; familiarity with business intelligence and analytical tools (like Business Objects, Tableau, SAS), advanced analytical and data science toolkits
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