Data & Analytics
Your data infrastructure is only as valuable as the decisions it enables.
We place the specialists who turn data infrastructure into operational intelligence. Engineers who build systems where data doesn't just report what happened. It drives what happens next.
The Execution Gap
You don't have a data problem. You have a value extraction problem.
The investment is already made. Snowflake, Databricks, Palantir Foundry, or a modern lakehouse sitting on top of years of cloud migration work. The platform is there. But the business still can't get a clean answer to a straightforward question without a three-day ticket cycle.
That's not a tooling failure. It's a talent architecture failure. Data engineering in 2026 has moved from pipeline developer to platform architect - and most teams still have the former when they need the latter.
Platform purchases that never reach full utilization because no one owns the ontology layer
AI initiatives stalled because the data foundation they depend on isn't production-ready
Foundry deployments that passed implementation but never reached operational intelligence
Analytics teams producing reports instead of decisions because the infrastructure can't support real-time insight
The Specialist
What an Elios data specialist actually does
Our data engineers aren't generalists who have touched your platform. They're architects who have built on it - designed ontologies, engineered pipelines at scale, integrated enterprise systems, and built the governance frameworks that make the data trustworthy enough to act on.
The 2026 data engineer sits at the intersection of infrastructure strategy and AI readiness. They understand that a data platform isn't complete when the pipelines run. It's complete when it feeds production AI systems, surfaces real-time operational insight, and holds up under regulatory scrutiny. We place engineers who operate at that level.
For Palantir Foundry specifically: we place engineers who have done this work inside Foundry before - ontology modeling, pipeline architecture, AIP integration, and the full operational deployment cycle. Not engineers learning the platform on your timeline.
Not a Generalist
What makes this different
Strong on SQL, weak on platform architecture
Matched to your specific platform at production depth
Builds pipelines, hands off governance
Owns infrastructure, governance, and AI readiness end to end
Generic data engineering background
Platform specialists: Foundry, Snowflake, Databricks, or modern lakehouse
Ramp time measured in months
Domain-matched and contributing in days
Measured by pipeline uptime
Measured by decisions the data enables
How It Works
Data infrastructure only creates value when it drives decisions.
Scope
We map your data environment: platform, pipeline maturity, and the gap between what exists and what the business needs to act on.
Source
Data engineers, architects, and analytics specialists matched to your specific stack and data maturity level.
Deploy
Integrated into your data team. Contributing to pipelines, platforms, and reporting systems from day one.
Deliver
Data systems that move from reporting what happened to driving what happens next.
“Domain practitioners evaluate candidates the way you would.”
How You Bring One On
Data specialists are available across all three Elios engagement models.
Talent on Demand
You know what you need: a Foundry engineer, a Snowflake architect, a streaming data specialist. We find the right person, pre-vetted against your platform and requirements, and you manage them directly.
Best when you have the infrastructure to onboard and direct a senior data engineer.
Embedded Teams
You're building a data platform from scratch or modernizing a legacy architecture. We design the team composition and deliver the right mix of data engineers, platform architects, and governance specialists structured to actually ship.
Best when the problem is bigger than a single hire.
Managed Delivery
You have a defined data outcome - a Foundry deployment, a lakehouse migration, an AI-ready data layer - and don't want to manage the team to get there. We scope it, staff it, and own the result.
Best when you want data outcomes without managing the team to get there.
Not sure which fits? Request a Consultation and we'll tell you straight.
Who This Is For
Who this is for.
Enterprises with Palantir Foundry Deployments
You bought Foundry. The implementation ran. But the platform isn't producing the operational intelligence the business case promised. An Elios Foundry specialist embeds in the gap between what the platform is configured to do and what your operations actually need - and closes it without restarting discovery. We've done this before, on Foundry, at this scale.
Organizations Building AI on Unready Data
Your AI roadmap depends on data infrastructure that isn't production-ready. Models training on inconsistent data produce inconsistent decisions. The AI initiative won't deliver until the data layer does. We place data architects who build AI-ready infrastructure - governed, reliable, and designed for the systems sitting above it.
Companies Modernizing Legacy Data Architecture
You're migrating off legacy warehousing into a cloud-native or hybrid lakehouse model. The platform strategy is set. The gap is the engineering depth to execute it without losing eighteen months of data credibility in the process. We place engineers who have run this migration before and know where the bodies are buried.
Data that doesn't drive decisions is just storage. We place the engineers who close that gap.
Data that doesn't drive decisions is just storage.
Tell us the platform and the gap. We'll match the right specialist.