Note: The job is a remote job and is open to candidates in USA. Acceldata is seeking a dynamic and results-oriented Sales Engineer to join our high-performing team. As a Sales Engineer, you will play a crucial role in driving the success of our Acceldata solutions by serving as the technical expert and a key liaison between our customers and the sales team.
Responsibilities
- Collaborate with Acceldata Account Teams, Product, and Customer Support teams to help prospects, customers, and partners identify the value and need for Acceldata solutions
- Develop, customise, and conduct technical presentations and product demonstrations to prospective customers, showcasing our solutions and how they address specific customer needs and challenges
- Proficiency in multiple Hadoop components (HDFS, Yarn, Spark, Hive, HBase, Ranger, Kerberos, Kafka, Zookeeper, etc.) & their working architecture, usage & workflow
- Hands-on experience with at least one of the following: Apache Spark, Trino, Jupyter and Airflow
- Partner with the Enterprise and Strategic Accounts teams to identify prospects’ environments and technical requirements to pursue tailored sales strategies, providing technical expertise to help close deals effectively
- Work closely with customers to design and develop solutions tailored to their data environments and technical requirements
- Develop comprehensive technical proposals & assist with crafting statements of work (SOWs)
- Lead the implementation of POCs to demonstrate the value & functionality of our products in the customer's environment. Analyze results & present value-oriented results to stakeholders
- Support from professional services and engineering will be provided as needed for technical expertise, closing gaps, or handling large or long-term engagements and pilots
- Provide internal support to sales, presales, marketing, partner and product teams. This includes marketing content development, demo asset creation, field intelligence, training, subject matter expertise, etc. to drive company success
- Educate the sales team on the technical aspects of data observability solutions, enabling them to effectively communicate product value to customers and prospects
- Assist in the development and maintenance of technical documentation, including product guides, technical specifications, and knowledge base articles, to aid customers and internal stakeholders in understanding and utilizing the data observability solutions
- Partner with AE’s and sales managers to ensure deal qualification - making sure a strong solution and technical fit before significant technical investment
Skills
- 12+ years of experience in a SaaS and Data Industry Sales Engineering role
- Bachelor's degree in computer science, engineering, data science, or a related field
- Hands-on experience with at least one of the following CSVs: AWS, GCP, and/or Azure
- Hands-on experience with cloud platforms, including Databricks or Snowflake
- Hands-on experience with data observability, data monitoring, data integration, and/or data quality products
- Strong understanding of data observability trends, challenges, & opportunities in the industry
- Strong understanding of the data ecosystem, including data warehouses, data lakes, and streaming data architectures
- Excellent communication and presentation skills to effectively convey complex technical concepts to both technical and non-technical audiences
- Ability to listen to customer needs, understand their pain points, and propose relevant data observability solutions
- Ability to analyze customer data scenarios & recommend suitable observability strategies
- Growth mindset - learn from mistakes, stay positive, find a path to win, look to the future, learn from the past
- Proactive self-starter with inherent motivation to meet and exceed performance goals
- Ability to work in a fast-paced and dynamic team environment
- Travel up to 50% meeting with qualified prospects as well as customers
- Willingness to do 'whatever it takes' to WIN
- Proficiency in multiple Hadoop components (HDFS, Yarn, Spark, Hive, HBase, Ranger, Kerberos, Kafka, Zookeeper, etc.) & their working architecture, usage & workflow
- Hands-on experience with at least one of the following: Apache Spark, Trino, Jupyter and Airflow
Company Overview
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