BI & AI Context Engineer

Motolite Marketing Corp.; Quezon City; On-site; PHP 1,000,000 - 1,500,000; Full time

Job summary

Motolite Marketing Corp. in the Philippines is seeking a BI + AI Context Engineer to translate trusted data into consistent metrics and decision-ready dashboards. You own the enterprise ontology and metric layer that underpins dashboards and AI answers.

You will work with Data & AI Translators and business experts to encode definitions, enable self-service analytics, and deliver production dashboards with Genie Spaces and NL analytics.

Qualifications

• Bachelor's degree in a related field as listed.
• Three+ years in BI, semantic modelling or analytics engineering.
• Preferred: Power BI Data Analyst Associate, Databricks fundamentals; optional dbt certifications.

Responsibilities

• Define metric views, semantic models and KPI logic as the single certified definition for measures.
• Build and optimize executive and self-service dashboards; design AI-ready dashboards with no manual refresh.
• Establish benchmarks, datasets and accuracy thresholds for NL analytics and Genie Spaces.
• Collaborate with Data Engineers, translators and business owners to encode definitions and rules.
• Monitor adoption and usefulness of delivered analytics products.

Skills

Analytical thinking

Attention to detail

Collaboration

Problem solving

Communication

Education

Bachelor’s degree in Computer Science, Information Systems, Statistics, Engineering, Business Analytics or a related field

Tools

Power BI

Databricks

Genie Spaces

Ontology design tools

Python

Job description

_ Join us and contribute to driving excellence at MOTOLITE! _

Job Summary:

The BI + AI Context Engineer converts trusted data into consistent metrics, business-ready semantic context, natural-language analytics and decision-oriented dashboards. The role owns the enterprise ontology and metric layer that makes both dashboards and AI answers correct and consistent.

3. Key Duties and Responsibilities

Semantic and metric layer

• Define metric views, semantic models, KPI logic and business glossaries as the single certified definition of each measure.
• Create, improve and expand the scope of context and the Ontology for Genie.
• Prevent conflicting calculations across dashboards, Genie Spaces, reports and AI applications.

Decision products

• Build and optimize executive dashboards, operating dashboards and self-service analytical products.
• Create and manage automated, AI-ready dashboards that require no manual refresh or manual reconciliation.
• Design for the decision being made, not for the data that happens to be available.

Evaluation and trust

• Establish benchmark question sets, evaluation datasets, accuracy thresholds and usage monitoring for Genie Spaces and natural-language analytics.
• Test and publish answer accuracy, and remediate where accuracy falls below threshold.
• Monitor adoption and retire or rebuild products that are not used.

Business partnership

• Work with Data & AI Translators and business experts to encode definitions, exceptions, decision rules and narrative context.
• Support user enablement and self-service capability building.

4. Key Deliverables

• Certified KPI and metric definitions and the enterprise business glossary.
• Semantic models and the Genie ontology.
• Production dashboards and self-service analytical products.
• Evaluated Genie Spaces with published accuracy benchmarks.
• Adoption and usage metrics.

5. Accountability and Success Measures

• Metric consistency across every consumption channel.
• Accuracy of natural-language and AI-generated answers within the assigned scope.
• Analytical usability and decision relevance of delivered products.
• User adoption of dashboards and self-service tools.
• Currency of definitions as the business changes.

6. Working Relationships

• Internal: Data Engineers; Data & AI Translators; Data Scientists; AI / LLM Engineers; Data Governance Specialist; business owners; BI & Context Engineering Capability Head.
• External: platform vendor support.

7. Qualifications

Education

Bachelor’s degree in Computer Science, Information Systems, Statistics, Engineering, Business Analytics or a related field.

Experience

Three or more years in business intelligence, semantic modelling or analytics engineering. Demonstrated ownership of enterprise metric definitions. Experience with natural-language analytics or LLM-based query interfaces is a strong advantage.

Certifications

Preferred: Power BI Data Analyst Associate, Databricks fundamentals. Optional: dbt or analytics engineering certification.

8. Technical Skills

• Advanced SQL; dimensional and semantic modelling.
• Power BI, including semantic models, DAX and performance optimization.
• Databricks, Unity Catalog metric views and Genie Spaces.
• Ontology and business-glossary design.
• Evaluation design for natural-language analytics — benchmark sets, accuracy measurement, regression testing.
• Visualization and dashboard design principles.
• Python for evaluation and automation is an advantage.

9. Behavioural Competencies

• Precision about definitions; refuses ambiguity in metrics.
• User empathy and design sense for decision support.
• Ability to interrogate business experts and extract tacit rules.
• Scepticism about AI-generated answers and a habit of verifying.
• Collaboration across engineering and business.

10. Level Guidance

Levels below are indicative and subject to OD and HR job evaluation.

BI + AI Context Engineer

Builds and maintains assigned dashboards, metrics and Genie Spaces. Three or more years of relevant experience.

Senior BI + AI Context Engineer

Owns the semantic layer for a domain, sets evaluation standards, mentors others. Six or more years of relevant experience.

Lead BI + AI Context Engineer

Owns the enterprise ontology and metric governance and deputizes for the Capability Head. Nine or more years of relevant experience.

“Motolite offers you not just a job, but a career with boundless opportunities”