Senior Solutions Architect, EMEA

London, England, United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Data & AI, Enterprise SoftwareIndustries

Requirements

Candidates should have 3-5 years of experience in a technical, customer-facing role, preferably within the data technology space, and a firm understanding of cloud data warehousing, data lakes, ETL concepts and workflows, BI solutions, SQL, and working with APIs. Networking experience is a plus, and prior experience working with Enterprise customers and managing multiple stakeholders and priorities is desired. Experience identifying and improving internal and customer-facing processes, and working in a startup environment, are also beneficial.

Responsibilities

As a Senior Solutions Architect, the individual will be a strategic technical counterpart to the Success team, defining project scope, guiding clear outcomes, and communicating technical and value propositions to customers. They will deliver implementations of Monte Carlo, including complex data lake environments, define best practice approaches for achieving desired technical capabilities, deliver training and enablement on advanced technical concepts, create collateral and documentation, and advocate on behalf of customers cross-functionally with Product, Engineering, Support, and Sales. Additionally, the role involves analyzing customer trends and identifying opportunities to drive product consumption growth.

Skills

Data Infrastructure

Customer-Facing

Technical Solutions

Data Lake

Technical Documentation

Product Enablement

Cross-Functional Communication

Problem-Solving

Monte Carlo Data

Provides end-to-end data observability solutions

About Monte Carlo Data

Monte Carlo Data helps businesses ensure the reliability of their data through end-to-end data observability, allowing real-time monitoring of data freshness, volume, schema, and quality. Their platform includes tools for incident detection and resolution, which assist analysts in addressing data quality issues efficiently. By integrating with communication tools like Slack and JIRA, it fits seamlessly into existing data management processes. The goal is to help businesses avoid the costs associated with bad data, making it suitable for data-dependent companies across various industries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$229.6MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

201-500Employees