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Indicium AI

Forward Deployed Data Engineer - Houston

Houston$180k–$230kmidAdded today

About this role

Serve as the principal technical authority embedded in high-stakes enterprise client environments, leading cloud-native Lakehouse modernization initiatives and agentic AI integration across Financial Services and Healthcare. Bridge C-suite strategy with hands-on production engineering, architecting complex data systems and guiding nearshore engineering teams to rapid delivery alongside Databricks and Anthropic partnerships.

What you'll do

  • Act as embedded technical lead on client engagements, partnering with VP/CTO stakeholders to architect solutions and translate complex requirements into execution plans
  • Write and optimize production PySpark, Databricks SQL, and Delta Live Tables code while refactoring legacy systems (Informatica, PL/SQL) into Medallion Architectures
  • Architect secure, deterministic data harnesses integrating LLM workflows (Claude/Anthropic) into enterprise pipelines
  • Provision cloud environments using Terraform, manage governance and lineage via Unity Catalog, and enforce CI/CD practices
  • Lead and mentor nearshore engineering squads through code reviews, performance optimization, and technical escalations
  • Provide 24/7 technical unblocking to resolve production issues and maintain delivery momentum

What they're looking for

  • Python and advanced SQL
  • Databricks platform (Delta Lake, PySpark, DLT, Unity Catalog, Workflows)
  • dbt for data modeling
  • Terraform and Infrastructure as Code
  • Git and version control
  • Data architecture and design patterns
  • LLM integration and AI workflows
  • Cloud platforms (AWS/GCP)
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Indicium AI

Indicium AI builds scalable data pipelines and infrastructure that support enterprise AI initiatives, including data integration, warehouse implementation, and ELT processes. The company is hiring Data Engineer Consultants to design and deliver production-grade data solutions while managing cloud infrastructure across cross-functional teams.

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Likely interview questions

  • Walk us through your most complex Databricks Lakehouse project—how did you design the Medallion Architecture and optimize performance at scale?
  • Describe a time you had to refactor legacy ETL logic (Informatica, stored procedures) into modern cloud-native code. What challenges did you face?
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