Data+Analytics

Elliot builds the data infrastructure, pipelines, and analytics layers that let your organization stop guessing and start knowing. We work across the modern data stack, including Snowflake, Databricks, BigQuery, and Redshift, with AI-native pipelines and agentic systems built on top.

Pipelines your team can trust and maintain

Most data problems are not analytics problems. They are infrastructure problems. Elliot builds the foundational layer: ingestion, transformation, orchestration, and quality, so that everything downstream delivers real insights.

Data Engineering + Pipelines

  • ETL/ELT pipeline architecture that is documented, tested, and not held hostage
  • Data quality frameworks and observability built into every layer
  • Processing designed around how your teams actually use data

Analytics + BI

  • Dashboard and reporting architecture that leadership actually uses
  • Semantic layers and governed metrics so every team works from the same numbers
  • Modern BI in Looker, Tableau, or Mode, with migration off legacy tools when the platform is the bottleneck

AI + Machine Learning

  • Vector databases, embedding pipelines, and RAG architecture for retrieval-augmented systems
  • Production ML deployment, monitoring, and retraining pipelines built into your data platform
  • Agentic systems that work directly against your enterprise data, with the right guardrails and access controls

Datainfrastructurebuilttocompound

Every Elliot data engineer has built production systems in environments where accuracy and uptime are non-negotiable. We carry that discipline into every engagement: pipelines designed to last, architecture that survives strategy shifts, and a foundation that stays useful as your organization scales.

AI-Ready by Default

Every pipeline we build is structured for AI consumption from day one. Vector embedding, semantic chunking, and access controls baked in, so when your team is ready to put AI on top of the data, the foundation is already there.

Documented, Tested, Owned

Pipelines come with the documentation, tests, and runbooks your engineers need to operate them without us. No tribal knowledge. No vendor lock-in. The codebase ships with the engagement.

Built for the modern data stack

Modern data tooling, not whatever was popular when we started. We work in Snowflake, Databricks, BigQuery, dbt, Airflow, and the modern data stack your team actually uses, with the AI layer that increasingly sits on top.