Senior Data, BI and AI Developer

Job Code
DataBI-AI-0926
Location
Remote
Terms
Contract / Project-Based • Senior • Approximately 3 Months
Salary/Rate
Depends on Experience
Skills Required
Power BI, Tableau, Business Intelligence, Data Visualization, Data Engineering, SQL, Python, ETL/ELT, Data Modeling, Data Quality, AI, Generative AI, Natural Language Querying, Predictive Analytics, Scenario Modeling, APIs

Job Overview

LABUSA is seeking a Senior Data, BI and AI Developer to design and develop secure, interactive data analytics and visualization solutions using information from multiple sources.

The position combines data engineering, business intelligence, dashboard development, and AI-enabled analytics. The successful candidate will transform complex datasets into reliable data models, interactive dashboards, decision-oriented visualizations, and natural-language data exploration capabilities.

Responsibilities

  • Assess, clean, validate, standardize, and transform datasets from multiple sources.
  • Design scalable data models supporting analytics, reporting, and visualization.
  • Develop ETL/ELT workflows and reusable data-transformation processes.
  • Implement data-quality checks and identify anomalies, missing information, inconsistencies, and reporting gaps.
  • Develop interactive BI dashboards and analytical reports.
  • Create visualizations for KPIs, trends, targets, geographic comparisons, demographics, and other business measures.
  • Implement filtering and drill-down capabilities by time period, geography, category, demographic variables, and other dimensions.
  • Develop time-series analytics and progress-against-target visualizations.
  • Implement AI-enabled data exploration using natural-language queries.
  • Develop scenario-modeling capabilities that allow users to adjust assumptions and evaluate potential outcomes.
  • Integrate AI/LLM capabilities securely with approved enterprise data sources.
  • Implement appropriate safeguards to reduce inaccurate or unsupported AI-generated responses.
  • Optimize dashboard performance and usability.
  • Support dashboard UAT, data validation, troubleshooting, and refinement.
  • Prepare technical documentation covering data models, transformation processes, configurations, and update procedures.
  • Support deployment, training, and technical handover.

Skills and Qualifications

Required Skills and Qualifications

  • Bachelor's degree in Data Science, Computer Science, Statistics, Information Systems, Engineering, Mathematics, or a related technical discipline.
  • 3 to 5+ years of professional experience in business intelligence, data analytics, dashboard development, or data engineering.
  • Advanced proficiency with at least one major BI/data visualization platform.
  • Strong SQL and data-modeling skills.
  • Experience cleaning and transforming complex datasets from multiple sources.
  • Demonstrated ability to develop interactive dashboards with filters, drill-downs, time-series analysis, and geographic or categorical disaggregation.
  • Experience implementing data-validation and quality-assurance processes.

Preferred Qualifications

  • Advanced Microsoft Power BI experience, including Power Query and DAX.
  • Python experience using common data-analysis and AI libraries.
  • Experience with Azure, AWS, or comparable cloud data platforms.
  • Experience integrating large language models or generative AI into enterprise applications.
  • Experience implementing retrieval-augmented generation (RAG), natural-language-to-SQL, or conversational analytics.
  • Experience developing forecasting or scenario-modeling applications.
  • Knowledge of role-based access control and enterprise data security.
  • Experience with development-sector, socio-economic, financial inclusion, employment, MSME, or international program data.

Additional Requirements

Ideal Candidate

The ideal candidate is equally comfortable working with raw datasets and presenting polished analytical products. The candidate should understand that reliable AI analytics begins with well-structured, validated data and should be capable of transforming complex information into intuitive tools for non-technical decision-makers.

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