Business Intelligence & AI Context Engineer

Hammerjack Pty Ltd; Philippines; On-site; PHP 1,000,000 - 1,400,000; Full time

Job summary

Hammerjack Pty Ltd seeks an experienced analytics engineer to define metric views and semantic models, building scalable dashboards and AI-ready analytics products. You will collaborate with Data & AI Translators and business experts to codify definitions and decision rules within the Genie ontology.

You will ensure accurate NLP-driven answers, monitor adoption, and continuously improve dashboards and self-service capabilities across enterprise datasets.

Qualifications

• Bachelor's degree in a related field is required.
• Three or more years in business intelligence, semantic modelling or analytics engineering.
• Experience with natural-language analytics or LLM-based query interfaces is a strong advantage.
• Power BI/Data Analytics credentials (preferred) or relevant certifications.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• Produce certified KPI and metric definitions and the enterprise business glossary.
• Develop semantic models and the Genie ontology.
• Deliver production dashboards and self-service analytical products.
• Evaluate Genie Spaces with published accuracy benchmarks.
• Track adoption and usage metrics.

Skills

BI analytics

Semantic modelling

Analytics engineering

Natural-language analytics

LLM interfaces

Education

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

Tools

Power BI

Databricks

Unity Catalog

Genie Spaces

DBT

Python

SQL

Job description

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.

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.

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.

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.

Qualifications.

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


• 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.


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

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.