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Key Responsibilities and Required Skills for BI Developer

💰 $70,000 - $110,000

TechnologyBusiness IntelligenceData AnalyticsSQLPower BITableauData WarehousingETLReportingBI Development

🎯 Role Definition

As a BI Developer, you will play a pivotal role in enabling data‑driven decision‑making across the organization by designing, developing, deploying and maintaining business intelligence solutions. You will partner with business stakeholders, data engineers, analysts and IT teams to transform raw data into insightful dashboards, reports and data models that drive operational and strategic outcomes. You will be responsible for the end‑to‑end lifecycle of BI systems — from requirement gathering and data‑warehouse design through to visualization, maintenance and continuous improvement of BI platforms.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Data Analyst or Reporting Analyst
  • SQL Developer or Database Engineer
  • Junior BI Developer

Advancement To:

  • Senior BI Developer or Lead BI Developer
  • BI Architect or Analytics Platform Lead
  • Director of BI / Head of Analytics

Lateral Moves:

  • Data Engineer specialising in ETL/Data‑Warehouse or Big Data
  • Analytics Engineer / Insights Engineer
  • Data Scientist focusing on dashboards, models and visualization

Core Responsibilities

Primary Functions

  1. Collaborate with business stakeholders to gather, clarify and document business intelligence requirements, translating them into functional and technical specifications for BI solutions.
  2. Design, build and maintain data‑warehouse design, data marts, semantic layers and dimensional models to support business intelligence, reporting and analytics activities.
  3. Develop, optimise and maintain extract‑transform‑load (ETL/ELT) pipelines that extract data from multiple sources, transform it according to business rules and load into BI data stores.
  4. Create, deploy and maintain interactive dashboards, self‑serve reporting tools and visualizations using BI platforms (such as Power BI, Tableau, Qlik, Looker) to deliver actionable insights.
  5. Ensure data source integration from transactional systems, external feeds, logs or APIs and develop robust data‑ingestion and data‑processing workflows.
  6. Perform query and report performance tuning: optimise SQL, indexing, data‑model structures, and dashboards so that BI solutions deliver fast and responsive insights.
  7. Manage and maintain data‑quality, data‑integrity and governance frameworks: establish validation, cleansing, reconciliation, metadata management and data‑cataloguing processes.
  8. Monitor and maintain production BI systems: track usage, performance, error‑rates, system‑health and implement monitoring, alerts and root‑cause workflows.
  9. Collaborate cross‑functionally with IT, operations, analytics, finance and marketing teams to align BI deliverables with business goals and metrics (KPIs) while ensuring governance and compliance.
  10. Document architecture, data‑flows, ETL logic, BI dashboards, metadata and user‑guides to support maintainability, audit readiness and knowledge transfer.
  11. Provide support to business end‑users: troubleshoot BI reports, train users, gather feedback, iterate on reports and ensure the accuracy of dashboards and analytics output.
  12. Lead migration and enhancement initiatives: upgrade BI platforms, migrate from legacy systems, implement new tooling, cloud migrations for data‑warehouses/BI platforms.
  13. Develop semantic models, cubes or in‑memory data structures (e.g., OLAP) to support complex analytical queries and multi‑dimensional aggregation.
  14. Design and implement data governance, security and compliance controls: define access controls, data masking, encryption and auditing for BI systems.
  15. Drive continuous improvement of BI processes, tooling, automation, and self‑service capabilities to empower business users and reduce dependency on central IT.
  16. Estimate, plan and deliver BI projects: define scope, deliverables, timelines, dependencies, coordinate across teams and report on progress to stakeholders.
  17. Mentor and coach junior BI developers, share best practices, review code, dashboards, ETL logic and contribute to building a data‑driven engineering culture.
  18. Conduct impact analysis, predictive modelling or advanced analytics (when required) to identify trends, patterns and support strategic decision‑making.
  19. Manage stakeholder relationships: partner with senior leadership, translate business problems into analytic solutions and present findings, insights and recommendations in understandable form.
  20. Maintain awareness of BI technology trends and best practices (cloud data warehouses, real‑time analytics, data‑lakes) and propose strategic improvements to BI architecture and tool stack.

Secondary Functions

  • Support ad‑hoc data requests and exploratory data analysis for business units and analytics teams.
  • Contribute to the organisation’s data strategy, BI roadmap, and integration of BI architecture with enterprise data platforms.
  • Collaborate with business units (finance, operations, marketing) to translate data/analytics needs into engineering tasks.
  • Participate in sprint planning, backlog grooming, stand‑ups and retrospectives in data‑oriented agile teams.

Required Skills & Competencies

Hard Skills (Technical)

  • Strong proficiency in SQL (T‑SQL, PL/SQL) and experience designing and querying relational and/or columnar data stores.
  • Experience in data‑warehousing concepts, dimensional modelling (star schema, snowflake), ETL/ELT processes and data‑pipeline development.
  • Knowledge of BI/visualization tools such as Power BI, Tableau, QlikView, Looker or equivalent and experience developing dashboards/reports.
  • Proficiency in data‑integration and transformation: connecting data sources, APIs, flat‑files, cleaning and shaping data.
  • Familiarity with OLAP, in‑memory cubes, semantic layers, data marts and performance‑tuning of BI systems.
  • Experience with cloud platforms or big‑data environments (Azure, AWS, Snowflake, Databricks) and modern data architectures.
  • Proficiency with programming/scripting languages (Python, DAX, R, SAS, Java‑Script) or ETL tools to automate BI workflows.
  • Analytical skills: ability to analyze large datasets, spot trends, build KPIs and deliver insights that influence business decisions.
  • Documentation and technical‑writing skills: create architectural diagrams, metadata catalogs, data‑flow documentation and run‑books.
  • Experience with agile development processes, version control (Git, TFS), CI/CD for BI deliverables and collaborative development environments.

Soft Skills

  • Excellent communication: able to convey analytic insights and technical results to business stakeholders, translate complex data into actionable recommendations.
  • Collaboration and teamwork: work effectively across functionally diverse teams (business, IT, analytics, operations) to deliver BI solutions.
  • Ownership and accountability: take responsibility for the full lifecycle of BI modules—design, build, operate, maintain and monitor.
  • Problem‑solving and critical thinking: identify root causes of data issues, propose and implement solutions, streamline analytic workflows.
  • Adaptability and continuous learning: stay abreast of emerging BI tools, analytics trends, data‑governance practices and evolving business needs.
  • Time‑management and prioritisation: manage multiple BI deliverables, deadlines, business requests and technical debt in a dynamic environment.
  • Strategic mindset: align BI initiatives with organisational goals, anticipate future analytics needs, guide roadmap decisions and escalate risks proactively.
  • Mentorship and development: support junior staff, share best practices, facilitate learning and foster a high‑performance BI team culture.
  • Quality‑driven mindset: ensure deliverables are accurate, reliable, maintainable and scalable rather than just meeting deadlines.
  • Attention to detail: ensure data accuracy, correct modeling, effective visual design, immaculate documentation and compliance with governance standards.

Education & Experience

Educational Background

Minimum Education:
Bachelor’s degree in Computer Science, Information Systems, Data Science, Statistics, Mathematics or a related field.
Preferred Education:
Master’s degree in Data Science, Analytics, Business Intelligence or a related discipline is an advantage.
Relevant Fields of Study:

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

Experience Requirements

Typical Experience Range:
3 ‑ 6 years of BI development, reporting or data‑engineering experience working with dashboards, data‑warehouses and analytics.
Preferred:
Proven hands‑on experience building enterprise‑scale BI solutions, developing data warehouses and dashboards, working with self‑service analytics, performance tuning and mentoring less experienced BI professionals.

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