Deploy Engineer

Ometria•New York, NY

17h•Remote

About The Position

Working at the intersection of data engineering, marketing technology, and enterprise account management, you will be responsible for onboarding enterprise clients onto Ometria's agentic intelligence product, ΛTLΛS. This will range from identifying and connecting data sources through to training clients and ensuring the platform delivers ongoing value. You will act as a trusted technical partner for our clients, guiding them through data integration, validation, alerting, and documentation strategies. This is a deeply hands-on role that requires both strong technical capability and the ability to communicate clearly with enterprise stakeholders. You'll be part of a team of strategic retail marketing experts empowering leading enterprise businesses to harness the power of AI-driven intelligence. Ometria is a client Data and Experience Platform built for retail marketers to be the fastest route to sustainable growth. Ometria helps marketers plan and launch their most profitable campaigns twice as fast, increasing their client loyalty and CRM revenue with personalized marketing messages all throughout the client journey. Our platform combines the data unification and client insight of a CDP with an experience platform, letting retail marketers easily and efficiently create experiences their clients love across email, mobile, on-site, social, direct mail and more. Ometria is trusted by some of the fastest growing retail brands in the world such as Sephora, Boden, and Steve Madden. We have a team of over 120 Ometrians based in North America and Europe. We have raised $75m from leading venture capital funds across the world such as Infravia Capital Partners, Octopus Ventures, Summit Action, Sonae IM and many others.

Requirements

Minimum 5 years of technical account management or solutions architecture experience in an enterprise software organization, preferably in the Retail and Ecommerce space.
Hands-on experience with data warehousing platforms, particularly Biq Query, Snowflake and Databricks, including the ability to build and manage data integrations and custom connectors.
Excellent communication and stakeholder management skills, with the ability to engage confidently with enterprise clients across both technical and commercial functions.
Strong understanding of the marketing technology landscape — familiarity with the major platforms, what they are used for, and how data flows between them.
Experience in marketing programme management and client data management, with a solid grasp of how brands structure and leverage their marketing data.
Practical knowledge of identity resolution and CDP-type activities, including data unification, audience segmentation, and profile management.
AI engineering capability, with experience building or working with AI-driven data products, pipelines, or platforms.
A methodical, self-directed approach to work, with the ability to manage multiple client engagements simultaneously and prioritise effectively.

Responsibilities

Identify and assess the data sources relevant to each client's ΛTLΛS deployment, determining the most effective approach for connecting to each.
Assist clients in building custom connectors and data integrations, including working with data warehouses such as Snowflake and Databricks.
Support context gathering and data uploading into the ΛTLΛS product, ensuring completeness and accuracy.
Review semantic inputs and outputs for the ΛTLΛS product, ensuring data is accurately interpreted and surfaced.
Work with clients' QA and validation teams to develop and implement robust data validation strategies.
Monitor the platform's inputs and outputs on an ongoing basis, identifying and addressing any alerts or anomalies.
Train clients on the usage of the ΛTLΛS platform, tailoring sessions to different audiences including technical and marketing stakeholders.
Work with clients to define alerting and notification strategies that keep the right people informed at the right time.
Support clients in developing and maintaining their documentation strategy, ensuring knowledge is captured and accessible.
Act as a trusted technical advisor throughout the client lifecycle, building strong relationships with data, marketing technology, and QA teams.
Communicate technical concepts clearly and confidently with enterprise stakeholders, adapting your approach to the audience.