OVERVIEW

We are an industry-leading startup developing AI for consumer brands. Our solutions leverage machine learning, generative AI, agent-based systems, and graph technologies to get our customers to insights in seconds and to business impact in minutes using our products.

We are looking for a Data Architect to own the foundation everything else is built on, reporting to our Co-Founder & CAIO.

ROLE

As Data Architect, you will design and own the data platform that our AI products run on. You'll define how data enters our systems, how it's modeled, how it's governed, and how it's served to models, agents, and applications in production.

This is a senior, founding-level role. You will make the architectural decisions that determine how fast we can move for the next several years - schema and modeling standards, storage and compute strategy, data contracts between teams, and the governance practices that let us handle sensitive customer data responsibly. You'll work closely with ML engineers, backend engineers, and customer-facing teams, and you'll be hands-on: designing, building, and operating, not just diagramming.

RESPONSIBILITIES

Platform & Architecture
• Design and own our data architecture end to end: ingestion, storage, transformation, and serving across multiple cloud environments and deployment models.
• Define data models and semantic layers that support both analytical workloads and production ML/agent systems.
• Establish data contracts and interface standards between ingestion, ML, and application layers.
• Evaluate and select platform components, balancing capability, cost, and operational burden.

Pipelines & Reliability
• Build and operate scalable ingestion and transformation pipelines for diverse customer and third-party data sources.
• Implement orchestration and versioning practices (Airflow, dbt, Dagster, or similar) that make pipelines reproducible and debuggable.
• Instrument data quality, lineage, freshness, and observability so problems surface before customers find them.
• Design for graph and relationship-heavy workloads alongside conventional tabular data.

Governance & Trust
• Establish standards for data security, access control, retention, and privacy across customer datasets.
• Build the tooling and documentation that make correct usage the path of least resistance.
• Partner with engineering and customer-facing teams on onboarding new customer data safely and quickly.

Leadership
• Set technical standards and best practices for data at Sciemo, and mentor engineers as the team grows.
• Translate business and product requirements into architectural decisions with clear tradeoffs.
• Stay current with the data platform landscape and bring in what's genuinely worth adopting.

ALL ABOUT YOU
• Significant experience designing and operating production data platforms at scale.
• Deep expertise in data modeling - dimensional, normalized, and semantic layer design - and strong SQL.
• Strong Python and production-grade engineering practices; comfort with Spark or equivalent distributed compute.
• Hands-on experience with modern warehouse/lakehouse platforms and orchestration/transformation tooling (Airflow, dbt, Dagster, ZenML, Kedro, etc.).
• Experience supporting ML and AI workloads specifically - feature availability, training/serving consistency, and retrieval patterns.
• Working knowledge of graph data models and when they beat relational approaches.
• Practical experience with data governance, security, and privacy in a customer-data environment.
• Strong communication skills - able to explain architectural tradeoffs to technical and non-technical stakeholders alike.
• Startup adaptability and a bias toward shipping.

BENEFITS & PERKS

Check out our one pager!

LOCATION

Hybrid role based in New York City; open to remote U.S. candidates willing to travel monthly to our NYC office.