Field Engineer

Reposted 17 Days Ago
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New York, NY
In-Office
160K-180K Annually
Mid level
Software
The Role
As a Field Engineer, you will guide clients through technical evaluations during the sales process, leveraging your expertise in data engineering and architecture to demonstrate and advocate for Materialize's solutions.
Summary Generated by Built In
Who We Are:

Materialize is the live data layer for apps and AI agents. It lets your team use SQL to transform siloed operational data into up-to-the-second views of your business, helping you operate confidently in dynamic environments. Use Materialize to deliver fresh context to AI agents, power data-intensive UIs, and create low-latency, event-driven architectures that drive microservices and core business processes. Materialize is trusted by General Mills, Bilt Rewards, and Crane Worldwide Logistics to solve their most pressing operational data challenges while building a live data foundation for their AI transformation

Our team spans the US (with a NYC headquarters), Canada, and EMEA. 

Investors:

Kleiner Perkins, Redpoint Ventures and Lightspeed Venture Partners.

Role Overview:

As a Field Engineer, you will guide the technical evaluation phase in a hands-on environment throughout the sales process. You will be a key part of the sales team, acting as a technical advisor and working with the product team as an advocate for your customers in the field. You will help our customers achieve tangible outcomes with Materialize, establish a clear architectural vision, identify compelling use cases, and help our customers realize value. You'll grow as a leader in your field while finding solutions to our customers' biggest challenging problems. 

Key Responsibilities:
  • Pre- or post-sales experience working with external clients
  • As this is a broad and varied role, you will have proven expertise in data, such as data engineering, architecture, or data science
  • Experience demonstrating technical concepts, including presenting and white-boarding
  • Proficiency with SQL and some scripting languages like Python
What We’re Looking For : 
  • You will become an expert on cutting-edge streaming and database systems
  • Lead your clients through evaluating and adopting Materialize
  • Support your customers by authoring reference architectures, how-tos, and demo applications
  • Engage with the technical community (both internal and customer) by leading workshops, seminars, tradeshows, and meet-ups
  • Together with your Account Executive, you will form successful relationships with clients to provide technical and business value
  • Hybrid working environment (3x in our Astor Place Office per week)
Bonus points for:
  • Significant experience using SQL databases, Flink, Kafka, and other data infrastructure.
  • Prior experience with Kubernetes and container orchestration 
  • Experience working with high-performance, high-availability systems.

Salary: $160,00 - 180,000/year + Equity

The salary range provided in this job description should not be considered a guarantee or commitment. The actual compensation offered may vary based on individual qualifications objectively assessed during the application and interview process, including but not limited to the candidate’s:

  • Qualifications and relevant work experience
  • Educational background and credentials
  • Relevant skills and certifications
  • Geographic location
  • Market demands

Materialize reserves the right to adjust the salary range based on the candidate's specific circumstances and the overall compensation package.

We understand it takes a diverse team of highly intelligent, passionate, curious, and creative people to develop the exceptional product we are building. Our dynamic team has incredible perspectives to share, just as we know you do, and we take great pride in being an equal opportunity employer.

Top Skills

Flink
Kafka
Kubernetes
Python
SQL
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The Company
HQ: New York, NY
61 Employees

What We Do

Materialize simplifies application development with streaming data. Materialize is powered by Timely Dataflow.

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