Forward Deployed Engineer - Remote

Business Intelli solutions; Texas; On-site; USD 110,000 - 140,000; Full time

Job summary

Business Intelli Solutions seeks a hands-on data/analytics engineer embedded with customer business units to build, deploy, and optimize data pipelines, semantic definitions, and automated cloud workflows.

You will develop production-grade data foundations for analytics and conversational AI, leaving behind durable capabilities with thorough documentation for the client.

Qualifications

• Bachelor's degree in CS, engineering, data science or related field or equivalent practical experience.
• 2–5 years in data engineering, analytics engineering or BI development, incl. 1+ year hands-on LookML.
• Strong SQL and BigQuery; experience building/operating production data pipelines.
• Working software engineering practice: Git, code review, testing and CI/CD.
• Comfort embedding with customer teams, delivering in agile sprints, with clear communication.

Responsibilities

• Build and deploy LookML models, Explores, dashboards, data apps and BigQuery pipelines from development to production.
• Define governed metrics, dimensions and access controls in LookML; deliver LookML pattern examples for conversational search and semantic discovery.
• Build CI/CD for LookML, Dataform or dbt pipelines, scheduled deliveries and API integrations.
• Work in agile, sprint with customer analysts and engineers to unblock technical paths and secure early wins.
• Profile and tune query performance, model structure, caching and aggregate strategies.
• Co-develop with customer engineers, write documentation, and support train-the-trainer programs.
• Capture platform friction and feature gaps, relay them through vendor channels.

Skills

SQL

BigQuery

Communication

Agile / Scrum

Customer-facing collaboration

Education

Bachelor's degree in Computer Science, Engineering, Data Science or related field

Equivalent practical experience

Tools

LookML

Looker API/SDKs

Dataform

dbt

Git

Job description

Summary:

A hands-on engineer embedded directly with customer business units to build, deploy and optimize data pipelines, semantic definitions and automated cloud workflows. You will build production-grade data foundations for analytics and conversational AI, and leave behind durable, documented capability when the engagement ends.

Responsibilities

• Build and deploy: Develop LookML models, Explores, dashboards, data apps and BigQuery pipelines in customer development and sandbox environments, moving prototypes to production.
• Semantic definitions: Implement governed metrics, dimensions and access controls in LookML to the architecture blueprint; deliver LookML pattern examples for conversational search and semantic discovery.
• Workflow automation: Build CI/CD for LookML, Dataform or dbt pipelines, scheduled deliveries and API integrations that cut manual maintenance.
• Adoption sprints: Work in agile, team-by-team sprints with customer analysts and engineers to unblock technical paths and secure early wins.
• Performance optimization: Profile and tune query performance, model structure, caching and aggregate strategies.
• Enablement and handoff: Co-develop with customer engineers, write documentation, and support train-the-trainer programs that build internal champions.
• Field feedback: Capture platform friction and feature gaps and relay them through the appropriate vendor channels.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science or a related field, or equivalent practical experience.
• 2–5 years in data engineering, analytics engineering or BI development, including 1+ year of hands-on LookML.
• Strong SQL and BigQuery; experience building and running production data pipelines.
• Working software engineering practice: Git, code review, testing and CI/CD.
• Comfortable embedding with customer teams, handling ambiguity and delivering in agile sprints.
• Clear communicator with a collaborative, customer-first mindset.

Preferred

• Python, Dataform or dbt, Looker API and SDKs, Looker extension framework.
• Conversational analytics, AI assistants in BI and data warehouse tools, or agentic workflows built on a semantic layer.
• BI migration tooling; translating Tableau, Power BI or Looker Studio assets into LookML.
• Associate or Professional Data Engineer, or Looker certifications.