Field Engineer at Materialize

New York, New York, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, DataIndustries

Requirements

Pre- or post-sales experience working with external clients
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

Responsibilities

Become an expert on cutting-edge streaming and database systems
Lead clients through evaluating and adopting Materialize
Support 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, form successful relationships with clients to provide technical and business value

Skills

Key technologies and capabilities for this role

SQLPythondata engineeringdata architecturedata sciencestreaming systemsdatabase systemswhite-boardingpresenting

Questions & Answers

Common questions about this position

What is the salary range for the Field Engineer position?

The salary range is $160,000 - $180,000 per year plus equity, though actual compensation may vary based on qualifications, experience, location, and other factors.

Is this Field Engineer role remote or does it require office presence?

This information is not specified in the job description.

What skills are required for the Field Engineer role?

Required skills include pre- or post-sales experience with external clients, proven expertise in data such as data engineering, architecture, or data science, experience demonstrating technical concepts like presenting and white-boarding, and proficiency with SQL and scripting languages like Python.

What is the company culture like at Materialize?

The team spans the US (with NYC headquarters), Canada, and EMEA, focusing on collaborative work with sales and product teams to solve customers' data challenges while growing as a leader.

What makes a strong candidate for this Field Engineer position?

Strong candidates have pre- or post-sales experience with clients, expertise in data engineering/architecture/science, SQL and Python proficiency, plus bonus experience with SQL databases, Flink, Kafka, Kubernetes, and high-availability systems.

Materialize

Cloud-based operational data warehouse for real-time insights

About Materialize

Materialize provides a cloud-based operational data warehouse that delivers real-time insights for businesses. The platform is designed for tasks that require immediate action based on current data, enabling data teams to analyze and operate their businesses effectively. Key features include automation and alerting, which reduce manual work and delays, allowing for quicker responses to data changes. Materialize supports user-facing applications that need to react to real-time business conditions and caters to companies requiring real-time customer data for personalization and dynamic pricing. The platform also meets the needs of machine learning and artificial intelligence by offering continuously updated data. Materialize's business model focuses on providing sub-second updates and strong consistency, utilizing a specialized engine built on stream processing frameworks. The goal of Materialize is to empower businesses to make immediate decisions based on accurate and timely data.

New York City, New YorkHeadquarters

2019Year Founded

$97.8MTotal Funding

SERIES_CCompany Stage

Data & Analytics, Enterprise SoftwareIndustries

51-200Employees

Benefits

Company Equity

Risks

Redpanda's serverless platform may attract cost-conscious developers away from Materialize.

Confluent's partner program increases competition in real-time data streaming.

Intensified market competition as more companies adopt real-time data solutions.

Differentiation

Materialize offers real-time data processing with a simple SQL interface.

The platform provides sub-second updates and strong consistency for streaming data.

Materialize's engine is built on Timely Dataflow and Differential Dataflow frameworks.

Upsides

Growing demand for real-time data processing boosts Materialize's market potential.

Partnership opportunities with Confluent enhance Materialize's integration capabilities.

Separation of storage and compute improves scalability and performance.

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