Business Intelligence Consultant

Position Summary

• The Business Intelligence Analyst leads the design, development, and optimization of the core analytics layer supporting global client incentive and engagement solutions. Operating as a proactive builder rather than a ticket-taker, this role models complex datasets, develops scalable semantic layers, and delivers intuitive dashboards for internal teams and external enterprise clients. By integrating modern AI developer tools directly into daily analytics workflows, the analyst accelerates pipeline development, quality assurance, and automated reporting while ensuring full data governance and analytical accuracy.

Key Responsibilities

• Design, build, and maintain dimensional data models, semantic layers, and version-controlled SQL transformation pipelines with automated data-quality checks.

• Build and maintain high-performance enterprise dashboards, standardizing critical operational, engagement, and ROI metrics across internal and client-facing platforms.

• Leverage modern AI tools and agents to streamline SQL drafting, automate recurring report generation, and perform initial trend analyses while validating all outputs for precision.

• Translate ambiguous business requirements into actionable data specifications, delivering clear strategic insights and narrative recommendations to non-technical stakeholders.

• Partner with technical teams to drive BI modernization efforts, retiring legacy reporting structures and migrating workflows to modern cloud and columnar architectures.

• Establish robust data governance standards by maintaining comprehensive data dictionaries, metric definitions, and compliance with data privacy regulations.

Qualifications

• 3–5 years of progressive experience in business intelligence, analytics engineering, or data analysis within a B2B platform or software environment.

• Advanced expertise in relational database querying (specifically T-SQL) combined with strong dimensional data-modeling fundamentals (e.g., star schemas).

• Proven hands-on production experience designing, deploying, and maintaining semantic models and reporting suites in modern BI platforms (such as Power BI, Tableau, Sisense, or Looker).

• Demonstrated practical experience applying Python (e.g., pandas) for data analysis and pipeline automation, alongside version control via Git.

• Active, daily workflow integration of LLMs and generative AI tools for code development and analytics, paired with rigorous analytical verification standards.

• Strong consultative communication skills with the ability to lead end-to-end projects and explain complex data findings to cross-functional teams.

Preferred Qualifications

• Experience with modern transformation frameworks (such as dbt) and cloud data warehousing/storage architectures (e.g., Snowflake, cloud object storage).

• Familiarity with fast analytical/columnar database engines (such as DuckDB) or emerging agentic data frameworks.

• Prior exposure to legacy ETL workflows (such as SSIS) to assist with system migrations and modernization initiatives.

• Working knowledge of Agile collaboration tools (Jira, Confluence).

• Domain background in enterprise HR technology, workforce engagement platforms, or incentive programs.