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Key Responsibilities and Required Skills for Business Intelligence Consultant

💰 $80,000 - $150,000

Business IntelligenceDataAnalyticsBI Consultant

🎯 Role Definition

As a Business Intelligence Consultant you serve as the bridge between business stakeholders and data engineering teams to translate strategy into measurable, operational analytics. You will design and deliver scalable BI solutions, maintain data integrity, drive adoption of self-service analytics, and continuously optimize reporting performance to support business growth and strategic decision-making.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Data Analyst
  • Reporting Analyst
  • ETL / Data Engineer

Advancement To:

  • Senior Business Intelligence Consultant / Lead BI Consultant
  • BI Manager / Analytics Manager
  • Head of Analytics / Director of Business Intelligence

Lateral Moves:

  • Data Engineer
  • Product Analytics Manager
  • Data Science / Machine Learning Engineer

Core Responsibilities

Primary Functions

  • Gather, elicit, and document business requirements by partnering with cross-functional stakeholders (finance, sales, marketing, operations) to translate high-level goals into precise, testable BI specifications and prioritized analytics roadmaps.
  • Design and implement end-to-end reporting solutions, from source system extraction and ETL/ELT logic to dimensional data models and semantic layers that support self-service and governed BI.
  • Build, maintain, and optimize interactive dashboards and visualizations using leading BI platforms (Power BI, Tableau, Looker, Qlik) that clearly communicate KPIs, trends, and insights to executive and operational audiences.
  • Author complex SQL queries and performance-tuned database scripts to source, transform, and aggregate data for reporting needs, ensuring query efficiency and minimizing resource consumption.
  • Create and maintain data models (star/snowflake schemas), measures, and calculations (DAX, LookML, MDX) that ensure consistent metric definitions and trusted single sources of truth across the organization.
  • Implement and manage ETL/ELT pipelines using tools such as Azure Data Factory, AWS Glue, Matillion, or dbt to ensure reliable, auditable, and scalable data ingestion from multiple transactional and third-party systems.
  • Lead requirements-to-production delivery: develop prototypes, perform iterative user validation, conduct UAT, and deploy dashboards and reports to production BI environments with deployment controls and rollback strategies.
  • Drive data quality initiatives by defining validation rules, building anomaly detection checks, reconciling source-to-report lineage, and working with source system owners to remediate data issues.
  • Define and monitor KPIs and SLAs for reporting, data freshness, dashboard usage, and analytical performance; provide executive-level reporting packages and ad-hoc analysis as needed.
  • Collaborate with data engineering and cloud infrastructure teams to design secure, cost-effective data architectures using cloud warehouses (Snowflake, BigQuery, Redshift, Azure Synapse) and ensure BI solutions align with cloud governance.
  • Provide technical leadership for BI platform administration: manage access controls, workspace governance, dataset refresh schedules, metadata catalogs, version control, and performance monitoring.
  • Translate complex analytics into clear business recommendations and narratives; prepare slide decks and reports for executive reviews, board presentations, and stakeholder briefings.
  • Mentor and train BI consumers and junior analysts on dashboard best practices, metric interpretation, data literacy, and self-service capabilities to increase adoption and reduce ad-hoc reporting requests.
  • Implement and maintain documentation artifacts including data dictionaries, metric definitions, data lineage diagrams, architecture diagrams, and runbooks for troubleshooting and onboarding.
  • Perform root-cause analysis for data and dashboard anomalies; triage incidents, prioritize fixes, and communicate status and resolution plans to stakeholders in a timely manner.
  • Support change management by coordinating rollout plans, stakeholder communications, training sessions, and feedback loops to ensure new analytics solutions are adopted and measured for impact.
  • Design and enforce BI security and compliance policies: implement role-based access, data masking, encryption requirements, and ensure solutions meet regulatory standards (GDPR, HIPAA, SOC2) where applicable.
  • Evaluate and recommend BI tooling, middleware, and automation solutions; run proof-of-concepts for emerging technologies and influence procurement decisions to align with long-term analytics strategy.
  • Optimize cost and performance trade-offs by tuning queries, restructuring data models, scheduling refresh windows, and leveraging aggregation strategies to reduce compute and licensing costs.
  • Integrate third-party APIs, marketing platforms, CRMs, ERP systems, and other data sources to enrich analytics capabilities and provide a consolidated view of customer and operational metrics.
  • Partner with analytics and data science teams to operationalize ML models, deploy predictive and prescriptive analytics into dashboards, and track model performance and drift within BI reports.
  • Establish and maintain a culture of continuous improvement by monitoring dashboard usage, soliciting stakeholder feedback, and iterating on analytics solutions to increase ROI and business impact.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Assist in vendor evaluations and manage relationships with BI tool providers and consulting partners.
  • Maintain knowledge of industry trends, emerging BI patterns, and best practices to proactively recommend improvements.
  • Create training materials, quick reference guides, and hands-on workshops to accelerate user adoption and build data literacy across teams.
  • Participate in cross-functional forums to align analytics priorities with product, finance, and operations initiatives.
  • Conduct periodic audits of dashboards and datasets to retire unused reports and reduce technical debt.

Required Skills & Competencies

Hard Skills (Technical)

  • Expert SQL proficiency for complex joins, window functions, CTEs, and performance tuning across relational and cloud-native warehouses (Postgres, Snowflake, BigQuery, Redshift).
  • Hands-on experience building dashboards and visualizations with Power BI, Tableau, Looker Studio / Looker (LookML), or Qlik; strong portfolio of published reports.
  • Data modeling skills: dimensional modeling, star schemas, conformed dimensions, slowly changing dimensions, and best practices for analytical schemas.
  • ETL/ELT tooling and pipeline orchestration experience (dbt, Airflow, Azure Data Factory, AWS Glue, Matillion) and understanding of incremental loads and CDC patterns.
  • DAX and/or MDX proficiency for designing complex measures and time-intelligence calculations in Power BI/SSAS environments.
  • Familiarity with cloud data platforms and architectures: Snowflake, BigQuery, Redshift, Azure Synapse; understanding of cost/performance trade-offs.
  • Scripting and data manipulation in Python or R for data transformation, automation, and advanced analytics integration.
  • Experience with data governance, metadata management, data catalogs, and implementing role-based security and compliance controls (GDPR, HIPAA).
  • API integration and working knowledge of ingesting data from CRMs (Salesforce), marketing platforms (Google Analytics, Adobe), ERP systems, and SaaS applications.
  • Proficiency with version control (Git) and CI/CD practices for BI artifacts, and experience deploying artifacts across development/staging/production environments.
  • Strong Excel skills including pivot tables, Power Query, and advanced formulas for quick analysis and validation.
  • Familiarity with Agile methodologies, sprint planning, and Jira/Trello for task management and delivery tracking.

Soft Skills

  • Exceptional stakeholder management and business partnering skills — able to facilitate discovery workshops, negotiate priorities, and manage expectations with senior leaders.
  • Strong communication and storytelling skills: translate complex data into concise, persuasive narratives and executive summaries.
  • Analytical mindset and problem-solving orientation; comfortable working with ambiguous requirements and driving toward measurable outcomes.
  • Mentorship and team leadership capabilities; able to coach junior analysts and lead cross-functional project teams.
  • Attention to detail and quality focus — ensures accuracy, reproducibility, and traceability of analytics outputs.
  • Time management and prioritization skills — able to balance multiple projects, urgent ad-hoc requests, and long-term roadmap items.
  • Customer-centric approach with a focus on usability, adoption, and business impact of BI solutions.
  • Adaptability and continuous learning mindset to stay current with evolving BI tools, cloud technologies, and analytics methodologies.

Education & Experience

Educational Background

Minimum Education:

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

Preferred Education:

  • Master’s degree in Data Science, Business Analytics, MBA with analytics focus, or related advanced degree.
  • Professional certifications (Microsoft Certified: Data Analyst Associate, Tableau Desktop Specialist, Looker Analyst, Snowflake certifications) are a plus.

Relevant Fields of Study:

  • Computer Science
  • Data Science / Analytics
  • Information Systems
  • Business / Finance
  • Statistics / Mathematics

Experience Requirements

Typical Experience Range: 3 - 8+ years in BI, analytics, or data engineering roles depending on level (Consultant to Senior Consultant).

Preferred:

  • 5+ years designing and delivering enterprise BI solutions; demonstrable experience in at least one major BI tool and one cloud data warehouse.
  • Proven track record of partnering with business stakeholders to deliver measurable business outcomes through analytics.
  • Experience operating within regulated industries (healthcare, finance, manufacturing) or large enterprise environments is beneficial.
  • Portfolio of dashboards, data models, documented projects, or a Git repository demonstrating BI design and implementation.
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