About the Role
We’re looking for a talented Sales Engineer to join our Enterprise sales team. As an Enterprise Sales Engineer, you will work closely with our sales team to understand our Enterprise customers’ complex business needs and showcase how Fivetran’s data replication solutions can help them achieve their desired business outcomes. You will be responsible for providing technical expertise, identifying technical requirements, and supporting a regimented proof-of-value process throughout the sales cycle.
This is a full-time position based out of Ireland, Germany, France or the UK.
Technologies You’ll Use
AWS
GCP
Azure
Snowflake
BigQuery
Databricks
Kafka
Grafana
Linux
Windows
Python
Java
What You’ll Do
Work with Enterprise customers to understand their business, their use cases, and their data replication requirements
Develop and deliver technical presentations to Enterprise audiences
Ensure the technical win by running a tight proof-of-value process
Work closely with Fivetran’s Product and Engineering teams to ensure alignment of our solutions to Enterprise customer needs
Develop and maintain relationships with key Enterprise customers and partners
Stay up-to-date on the latest technologies and trends in our industry
Skills We’re Looking For
10+ years in data replication, sales engineering, or related technical field
Strong technical background covering database replication, cloud infrastructure, and data replication technologies
Experience with modern data analytics technologies, including cloud data warehouses, data lakes, transformation tooling, data catalogs, and BI tools
Excellent communication and presentation skills with a keen ability to explain complex technical concepts to both technical and non-technical stakeholders
Strong problem-solving and analytical skills
Bonus Skills
Experience with SAP or Oracle/SQL Server databases
Hands on experience with other data replication or ETL tools
Experience with self-hosted software applications and supporting infrastructure
Hands on networking experience both in the cloud and on-premise
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