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Key Responsibilities and Required Skills for BI Dashboard Developer

💰 $80,000 - $130,000

Business IntelligenceData AnalyticsSoftware DevelopmentReporting

🎯 Role Definition

The BI Dashboard Developer is a hands-on analytics engineer and visualization specialist responsible for translating business strategy into operational dashboards and self-service analytics. This role designs, builds, tests, optimizes and documents production-grade dashboards and reports (Power BI, Tableau, Looker, Looker Studio), builds or collaborates on ETL/ELT pipelines, implements data models in data warehouses (Snowflake, Redshift, BigQuery, Azure Synapse), and partners with product, finance, sales and operations to deliver actionable KPIs and insights. The ideal candidate balances strong SQL and data modeling skills with visual design, stakeholder communication and production deployment practices (CI/CD, version control, testing, monitoring).

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior BI Analyst / Reporting Analyst with 1–3 years of dashboarding experience.
  • Data Analyst or Business Analyst transitioning into visualization engineering.
  • ETL Developer or Data Engineer who has built reports and dashboards.

Advancement To:

  • Senior BI Developer / Lead BI Dashboard Developer
  • Analytics Engineering Lead or BI Manager
  • Business Intelligence Architect / Head of Data Visualization

Lateral Moves:

  • Data Engineer (analytics-focused)
  • Product Analytics or Growth Analytics roles

Core Responsibilities

Primary Functions

  • Design, develop and deliver intuitive, scalable BI dashboards and executive reports using Power BI, Tableau, Looker or Looker Studio that translate strategic business goals into measurable KPIs and visual narratives for senior leadership.
  • Gather and document detailed reporting requirements through stakeholder interviews, user stories and acceptance criteria; translate requirements into data models, wireframes and release-ready dashboards.
  • Build, optimize and maintain robust data models (star schema, slowly changing dimensions, conformed dimensions) in the data warehouse to support performant and accurate dashboard queries.
  • Author complex SQL (Postgres, Snowflake SQL, T-SQL, BigQuery) and tune queries to deliver fast, reliable results for interactive dashboards and scheduled reports.
  • Implement and maintain DAX and Power Query (M) logic for measures, calculations, and row-level security in Power BI reports ensuring accurate business metrics and aggregation behavior.
  • Create, maintain and optimize ETL/ELT pipelines (SSIS, dbt, Airflow, Matillion, Azure Data Factory) that prepare, transform and validate data feeding dashboards; ensure pipeline observability and retry patterns.
  • Define and maintain semantic layers and shared datasets to enable consistent metrics across reports and self-service analytics initiatives.
  • Apply visualization best practices: layout, color theory, accessibility, storytelling and user experience to improve insights adoption and reduce misinterpretation.
  • Implement row-level security (RLS) and role-based access controls to ensure data privacy and compliance in production dashboards.
  • Build automated tests, data validation checks and anomaly detection to guarantee the quality and integrity of dashboard data and underlying pipelines.
  • Work collaboratively with data engineering, product, finance and operations teams to prioritize dashboard backlog, drive feature scoping and coordinate cross-functional releases.
  • Deploy dashboards and reporting artifacts into production using source control (Git), deployment pipelines and release best practices, maintaining version history and rollback plans.
  • Monitor dashboard performance and usage metrics; proactively refactor slow visuals and queries, archive unused reports and drive cost efficiency in cloud queries and compute.
  • Deliver end-user documentation, quick-reference guides and training sessions to onboard business users and promote self-service analytics adoption.
  • Conduct UAT and gather iterative feedback from stakeholders; implement changes with an emphasis on measurable business outcomes and improved decision-making.
  • Partner with data governance to document and enforce metric definitions, lineage, metadata and a data catalog for transparent, auditable reporting.
  • Troubleshoot production incidents, triage data discrepancies and drive root-cause analysis to restore accurate reporting within SLA targets.
  • Estimate development effort, manage sprint tasks, and provide clear status updates to product owners and stakeholders in an Agile environment.
  • Mentor and review work of junior BI developers and analysts; provide guidance on dashboard design, query optimization and analytics best practices.
  • Evaluate third-party BI tools, visualization libraries and managed services and make recommendations to improve analytics capabilities and reduce technical debt.
  • Create and maintain a centralized KPI library and dashboard templates to accelerate new report development and ensure visual consistency across the organization.
  • Collaborate on instrumentation and event tracking strategies to ensure product metrics are captured accurately and available for analysis and reporting.

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.
  • Maintain data dictionaries, source-to-target mapping documentation and lineage diagrams to aid troubleshooting and governance.
  • Assist with vendor onboarding, license management and cost optimization for BI platforms and cloud analytics services.

Required Skills & Competencies

Hard Skills (Technical)

  • Power BI (including DAX, Power Query/M, paginated reports) — design, modeling, optimization and deployment.
  • Tableau Desktop & Server or Tableau Online — calculated fields, LOD expressions, performance tuning and dashboard actions.
  • Looker / LookML / Looker Studio experience for semantic modeling and exploration-based reports.
  • Expert SQL (PostgreSQL, Snowflake, BigQuery, T-SQL) — complex joins, window functions, CTEs, query optimization and explain plans.
  • Data modeling & dimensional design (star/snowflake schemas, fact and dimension design, SCD implementation).
  • ETL/ELT tools and pipelines — dbt, Airflow, SSIS, Azure Data Factory, Matillion or equivalent; ability to implement transformations in SQL/dbt.
  • Cloud data warehouse platforms — Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse.
  • BI deployment best practices — Git, CI/CD pipelines, semantic layers, version control and release management.
  • Data quality, validation and testing frameworks — automated checks, unit tests for data transformations and reconciliation processes.
  • Scripting and automation — Python, Bash or similar for data processing, automation and lightweight tooling.
  • Dashboard performance tuning and optimization — query optimization, aggregation tables, incremental refresh and indexing strategies.
  • Row-level security and access control — implementation and maintenance of secure access patterns.
  • API integration and JSON parsing — extracting metrics from REST APIs and integrating 3rd-party data sources.
  • Familiarity with analytics instrumentation and event tracking (Segment, Snowplow, GA) and their mapping to BI datasets.
  • Metadata, lineage and data governance tools — Collibra, Alation or equivalent, and practices for cataloging datasets.

Soft Skills

  • Exceptional stakeholder management — ability to elicit requirements, negotiate priorities and deliver business value.
  • Strong analytical and problem-solving mindset with attention to detail and data accuracy.
  • Excellent communication and presentation skills — translating technical findings into concise business recommendations.
  • Product-minded approach — focus on outcomes, measurability and iterative improvements.
  • Collaboration and teamwork — cross-functional work with product managers, engineers and business leaders.
  • Time management and prioritization — manage multiple dashboards, requests and sprint commitments.
  • Coaching and mentoring — develop junior team members and promote knowledge sharing.
  • Adaptability and continuous learning — staying current with BI tooling, cloud platforms and analytics trends.

Education & Experience

Educational Background

Minimum Education:

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

Preferred Education:

  • Master's degree in Data Science, Business Analytics, Computer Science, or MBA with analytics focus.
  • Certifications such as Microsoft Certified: Power BI Data Analyst Associate, Tableau Desktop Specialist, dbt Labs Certification or Snowflake certifications are a plus.

Relevant Fields of Study:

  • Computer Science
  • Data Science / Analytics
  • Information Systems
  • Mathematics / Statistics
  • Business Administration / Finance (with analytics emphasis)

Experience Requirements

Typical Experience Range: 3 - 7 years building and maintaining business intelligence dashboards and analytics solutions.

Preferred:

  • 5+ years of hands-on dashboard development (Power BI/Tableau/Looker) and SQL-based data modeling.
  • Proven experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and ETL/ELT orchestration (dbt, Airflow).
  • Track record of delivering production BI solutions, implementing RLS, and driving adoption of self-service analytics.
  • Experience working in Agile teams, participating in sprint ceremonies, backlog grooming and stakeholder demos.
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