FI
Lead Sales Engineer, Enterprise
FivetranRemote, Australia, APACPosted 15 April 2026
Tech Stack
Job Description
From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.
About the Role
As a Fivetran Lead Sales Engineer in Australia, you will drive massive transformation and efficiency for customers of all sizes in a booming market. Using your experience with Data Replication/Integration, ETL/ELT, cloud data warehousing, data lake houses, and analytics, you will skillfully guide prospects and partners to faster, more reliable, and secure data foundations for the AI world. You will be directly and enthusiastically supported by a world-class Sales Engineering team, an agile and hungry APAC Sales team, and a suite of products that enable companies to leverage AI workloads with successful data foundations.
This is a full-time position based remotely out of Australia.
What You'll Do
Work with Enterprise customers to understand their business, their use cases, and drive pre-sales discovery and solutioning engagements with all levels of enterprise audiences
Plan, manage, and effectively close out technical demonstrations and proof of concept (POC) projects, often serving as both the subject matter expert and project manager
Respond to technical enquiries including Requests for Informations (RFIs), Proposals (RFPs) and similar formal documents
Develop and maintain relationships with key Enterprise customers and partners
Enable Fivetran staff, partner teams, and the data engineering community at large on data concepts, product features, competitive positioning, and best practices; e.g. blog articles, group presentations, training sessions, recorded videos, one-to-one coaching etc.
Work closely with Fivetran’s Product and Engineering teams to ensure alignment of our solutions to Enterprise customer needs
Provide technical guidance and assistance to new customers to ensure successful adoption and scale
Be intimately familiar with and have a positive reputation within the Australia and New Zealand region.
Skills We're Looking For
8+ years in data replication, sales engineering, or related technical field
Experienced in Data Replication/Integration (CDC) tools
Solid knowledge of data lakes, lakehouses and scalable data foundations for AI use cases
Proficiency in SQL scripting
Knowledge in Python/JavaScript and Rest API interaction
Hands-on experience with modern databases (PostgreSQL, Oracle, SQL Server, MongoDB, SAP) in on-premise and cloud deployments.
Working knowledge with one or more major cloud providers (AWS, GCP, Azure)
Knowledge with modern cloud data warehousing providers ( Snowflake or Databricks) and data lake architectures (Iceberg, Delta etc)
Excellent communication and presentation skills with a keen ability to explain complex technical concepts to both technical and non-technical stakeholders
Passion for data and analytics, a philosophy of using technology to help solve business problems
Strong problem-solving and analytical skills
Curiosity to learn and assimilate technical information quickly, enthusiasm to share and teach others
Experience selling into and influencing multi-faceted decision-groups within large and complex organizations
#LI-REMOTE
#LI-MM1
Perks and Benefits
100% employer-paid medical insurance *
Generous paid time-off policy (PTO), plus paid sick time, inclusive parental leave policy, holidays, and volunteer days off
RSU stock grants*
Professional development and training opportunities
Company virtual happy hours, free food, and fun team-building activities
Monthly cell phone stipend
Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all cover ... (truncated, view full listing at source)
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