Business Intelligence Analyst

Position Summary:

The Business Intelligence Analyst will accelerate data‑driven decision making across IT by combining robust BI practices with modern AI and containerization workflows. This role builds and maintains analytics solutions (Power BI, SQL, Python), leverages Microsoft Copilot and Azure AI for productivity and insights and operationalizes BI assets using Docker (or similar technologies) with a strong focus on performance, reliability, and security in Linux environments. The ideal candidate is equally comfortable interpreting system and security data, optimizing container images via multi‑stage builds, and presenting concise insights to technical and executive stakeholders. This position reports directly to the Director of Cybersecurity & Information Technology.

Knowledge and Skills:

· Aptitude to learn new concepts and technologies quickly and with minimal direction.

· Ability to operate effectively, even when tasks are not clear, or project plan is not in place.

· Ability to work within a lean IT operating model with varying degrees of direction and supervision.

· Ability to build positive and effective working relationships across teams at various levels in the organization.

· Ability to multi-task and work well under pressure, managing projects, timelines, and stakeholders.

· Action-oriented and eager to embrace new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.

· Capable of building strong end-user relationships and delivering customer-centric service.

· Effective verbal and written communication skills with the ability to communicate with end-users and stakeholders in a professional, clear, and concise manner.

Duties and Responsibilities:

The Business Intelligence Analyst is responsible for executing the following job responsibilities:

Data, BI & Analytics

· Collect, clean, and analyze IT and cybersecurity datasets (e.g., system logs, SIEM events, endpoint telemetry, cloud metrics) to identify trends, risks, and opportunities.

· Design and maintain Power BI and/or Tableau dashboards for operations, reliability, and security KPIs (e.g., incident MTTR, patch compliance, SLA adherence).

· Author ad‑hoc analyses and executive summaries; translate complex findings into clear recommendations.

AI Enablement (Copilot & Azure AI)

· Integrate Microsoft Copilot (M365, Copilot for Power BI, GitHub Copilot) to boost analyst productivity (query generation, documentation, report narratives).

· Partner within the organization to deploy Azure AI services (Cognitive Search, Language, OpenAI) for automated insights (e.g., log summarization, anomaly detection, forecasting).

· Establish best practices for AI usage, prompt patterns, and responsible AI (data privacy, model limitations, guardrails).

Data Engineering & Modeling

· Build scalable data models (star/snowflake) and semantic layers tuned for BI performance.

· Develop ETL/ELT pipelines using SQL and Python (pandas); optimize queries, partitioning, and indexing.

· Implement data quality checks, lineage, and governance (naming conventions, access controls, sensitivity labels).

Containerization & Operationalization

· Package BI/analytics workloads with Docker; design multi‑stage builds to produce lean, secure images.

· Optimize container images (layer minimization, caching, dependency pruning, base image selection, CVE remediation).

· Orchestrate local and team environments using Docker Compose (service definitions, networking, volume management, env vars).

· Integrate container builds into CI/CD (image tagging, vulnerability scanning, registry management, artifact promotion).

Platform, Security & Reliability

· Operate on Linux (Ubuntu/RHEL/Alpine) or other relevant platforms for analytics tooling, scripting, and container runtimes.

· Collaborate with Cybersecurity to embed security controls (least privilege, secrets management, SBOMs, image signing).

· Monitor BI platform performance and cost; instrument telemetry and alerting (e.g., API latency, refresh failures).

Collaboration & Stakeholder Engagement

· Work cross‑functionally with IT Ops, SecOps, Apps, and Finance to prioritize requirements and deliver measurable outcomes.

· Present findings and roadmaps to leadership provide enablement sessions for BI and AI adoption.

Education and Experience:

Desired Education:

· Bachelor’s in information technology, Data Analytics, Computer Science, or related field; or equivalent experience.

Desired Experience:

· 3–5+ years in BI/IT analytics with demonstrated delivery of dashboards, models, and automations.

· Technical Skills:

o BI & Data: Power BI (DAX, dataflows, gateways), SQL (T‑SQL or PostgreSQL), data warehousing concepts.

o Linux: Command‑line fluency (filesystem, processes, services), shell scripting, permissions, networking basics.

o Python: Data analysis with pandas, data APIs, virtual environments; performance/profile‑aware coding.

o Docker: Authoring and optimizing Docker files (cache strategies, layer ordering, minimal base images).

§ Multi‑stage builds (separate build/runtime stages, artifact copying, image hardening)

§ Image security practices (non‑root users, read‑only FS, vulnerability scanning).

o Docker Compose: Service orchestration, dependency graphs, health checks, volumes, environment management.

o AI Tools: Hands‑on with Microsoft Copilot (M365/Copilot for Power BI/GitHub Copilot) and Azure AI services.

o Version Control & CI/CD: Git (branching, PRs), pipelines for test/build/scan/publish, registry (ACR/ECR/Docker Hub).

· Overall willingness to “roll-up your sleeves” to provide support for all facets of the organization’s Information Systems Ecosystem (Technology).

· Experience with Azure (Azure SQL, Synapse, Data Factory, Key Vault, ACR) or equivalent cloud platforms.

· Fundamentals of machine learning applied to IT operations.

· Exposure to Kubernetes (nice to have) for scaling analytics services.

· Certifications: Microsoft Certified: Power BI Data Analyst Associate, Azure Data Engineer, Azure AI Engineer, or related.

Key Competencies:

· Analytical Rigor: Connects signals across logs, metrics, and business outcomes; quantify impact.

· Operational Excellence: Designs reproducible, secure, and performant analytics environments.

· Communication: Clear storytelling to technical and non‑technical stakeholders.

· Innovation & Ownership: Proactively introduces AI and automation to reduce toil and improve reliability.

Other:

· Qualified applicants will be contacted.

· Relocation Assistance not provided.

· Physical Demands:

o Ability to sit and stand for long periods of time in front of a computer.

o Ability to lift, up to 25 lbs. independently, team lifting equipment as appropriate.

Pay: $95,000.00 - $115,000.00 per year

Benefits:

• 401(k) matching
• AD&D insurance
• Dental insurance
• Disability insurance
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid holidays
• Paid sick time
• Paid time off
• Retirement plan
• Vision insurance

Work Location: In person