
Sales Engineer (UK - Remote)
AcceldataPosted 3/10/2025

Sales Engineer (UK - Remote)
Acceldata
Job Location
Job Summary
Acceldata is seeking a dynamic Sales Engineer to join their high-performing team. As a Sales Engineer, you will play a crucial role in driving the success of their cutting-edge data observability solutions. You will collaborate with sales, product, finance, and support teams to identify customer needs and challenges, customize technical presentations and product demonstrations, and partner with sales to pursue tailored sales strategies. With 10+ years of experience in a relevant role, hands-on experience with cloud providers, and strong understanding of data observability concepts, you will be the technical expert and key liaison between customers and the sales team. Acceldata is an equal opportunity employer committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status or any other special status. Join a culture that values an ‘out-of-the-box’ mindset and provides employees with the right tools and resources to excel at their job.
Job Description
We’re looking for someone who can:
- Collaborate with Acceldata sales, product, finance, and support teams to help prospects and partners identify the value and need for Acceldata Products to drive sales.
- Customize and conduct technical presentations and product demonstrations to prospective customers, showcasing our solutions and how they address specific customer needs and challenges.
- Partner with sales 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 and assist with crafting statements of work (SOWs).
- Lead the implementation of proof of concepts to demonstrate the value and functionality of our products in the customer's environment. Analyze results and present findings to key 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.
- Develop and maintain 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.
What makes you the right fit for this position?
- 10+ years of experience in a relevant role.
- Bachelor's degree in computer science, engineering, data science, or a related field.
- Must have hands-on experience with at least one of the following cloud providers: AWS, GCP, and/or Azure.
- Must have hands-on experience with cloud platforms including Databricks or Snowflake.
- Must have a Hadoop background in presales, architecture, or support type of role.
- Must have a strong understanding of data observability, data monitoring, and data quality concepts.
- Familiarity with data observability trends, challenges, and opportunities in the industry.
- 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.
- Capacity to analyze customer data scenarios and recommend suitable data observability strategies.
- Proficiency in data technologies and tools such as SQL, Python, R, data visualization tools, and data analytics platforms is a plus.