Elastic is the world’s leading software provider for making structured and unstructured data usable in real time for search, logging, security and analytics use cases. Founded in 2012 by the people behind the Elasticsearch, Kibana, Logstash, and Beats open source projects, Elastic’s global community has more than 50,000 members across 45 countries, and since its initial release, Elastic’s products have achieved more than 50 million cumulative downloads. Today thousands of organizations like Cisco, eBay, Dell, Goldman Sachs, Groupon, HP, Microsoft, Netflix, NY Times, Uber, Verizon, Yelp, and Wikipedia use the Elastic Stack, X-Pack, and Elastic Cloud to power mission critical systems that drive new revenue opportunities and massive cost savings. Elastic is backed by $104 million in funding from Benchmark Capital, Index Ventures, and NEA; has headquarters in Amsterdam and Mountain View, California; and has over 300 employees in over 30 countries around the world.
You will have the opportunity to work with a tremendous services, engineering and sales team and wear many hats. This is a critical role, as Consultants have an amazing chance to make an immediate impact to the success of Elastic and our customers.
Responsibilities
Deliver Elastic solutions to drive customer business value from our products
Solution design, development, and integration on Elastic products and APIs, platform architecture, and capacity planning in mission-critical environments
Requirements gathering, architectural design, integrating with other enterprise technologies, and documenting solutions
Strong customer advocacy, relationship building, and communications skills
Comfortable working remotely in a highly distributed team
Development of demos and proof-of-concepts that highlight the value of the Elastic Stack
Data modeling, query development and optimization, cluster tuning and scaling with a focus on fast search and analytics at scale
Technology workshops that include hands-on mentoring, whiteboarding, and solution development
Solving our customers’ most challenging data problems
Working closely with the Elastic engineering, product management, and support teams to identify feature enhancements, extensions, and product defects
Engaging with the Elastic Sales team to scope opportunities while assessing technical risks, questions, or concerns
Mentoring Elastic team members on new technology and solutions
