Business Intelligence Analyst

Position Summary

We are seeking a proactive Business Intelligence Analyst (Power BI) to take full end-to-end ownership of our enterprise reporting and business analytics ecosystem. In this role, you will consolidate data across key platforms—including CRM, ATS, workforce management, time tracking, and financial systems—to deliver actionable, trusted insights that drive executive decision-making.

Reporting directly to the Client Services & Delivery leadership team, this is an individual contributor role focused on driving production reporting stability, auditing data discrepancies, and safeguarding key organizational metrics. You will step into an established ecosystem built on Snowflake and Power BI, managing executive suites and operational dashboards spanning pipeline efficiency, workforce utilization, service delivery, and retention metrics. Following a structured onboarding and knowledge transfer process, you will partner closely with operational and engineering teams, with future opportunities to contribute to data pipeline engineering and lakehouse analytics.

Key Responsibilities

Dashboard Management & Power BI Engineering

• Direct, monitor, and optimize scheduled dataset refreshes, Power BI Service workspaces, gateway configurations, access permissions, and semantic models.

• Design, build, and enhance interactive reports utilizing Power Query (M), DAX metrics, structured data modeling, and performance tuning techniques.

• Preserve dashboard reliability, clear labeling standards, and data alignment across executive and operational reporting tools.

• Diagnose and resolve gateway or data refresh anomalies before they affect business end-users.

Data Governance, Quality & Metrics Standardization

• Convert cross-departmental requirements into structured data models, business logic, and reporting features.

• Maintain and expand the central data dictionary, ensuring strict version control for changes in KPI logic or business definitions.

• Lead cross-functional alignment and communication whenever metric formulas or underlying methodologies are modified.

• Perform root-cause analysis on data discrepancies by auditing frontend visuals, semantic models, underlying SQL queries, data warehouse tables, and upstream transactional applications.

• Author, debug, and optimize complex SQL queries for multi-system reconciliation, validation, and data transformation.

Documentation & Process Continuity

• Build comprehensive technical documentation detailing data lineage, source mapping, logic dependencies, scheduled jobs, and troubleshooting protocols.

• Maintain complete documentation assets following onboarding sessions with technical stakeholders.

Stakeholder Partnership & Analytics Evolution

• Collaborate directly with U.S.-based leadership to scope, organize, and execute analytics initiatives using a structured product backlog.

• Proactively identify manual data processes, metrics ambiguities, and pipeline bottlenecks, presenting scalable automation solutions.

• Collaborate with data engineering to assist with upstream data aggregation, semantic layer optimization, and data-lake integration for future portal features.

• Leverage modern AI tools to accelerate SQL/DAX writing, documentation, and error resolution while critically validating all outputs.

Key Performance Expectations (First 90 Days & Beyond)

• Successfully complete transition training, gain full visibility into data flows, and autonomously oversee core production workspaces within 90 days.

• Proactively catch and resolve technical or data anomalies prior to internal stakeholder discovery.

• Keep definitions clear and updated in the data dictionary while maintaining consistent reconciliation between reports and source systems.

• Manage incoming analytical requests systematically, balancing backlog items according to organizational strategy rather than request volume.

• Surface operational insights, pipeline vulnerabilities, and data quality trends independently.

Qualifications & Experience

Required:

• 3–5 years of hands-on experience in business intelligence, data modeling, or analytics engineering within a production environment.

• Proven track record of managing and architecting production-grade Power BI semantic models (beyond basic frontend visual creation).

• Advanced proficiency reading, writing, debugging, and tuning SQL across relational data stores and modern warehouses.

• Practical exposure to enterprise data architectures, including dimensional modeling (star schema, snowflake schema, grain control, and calculated measures).

• Core capability in Power BI Desktop & Service: DAX, Power Query/M, RLS, workspace deployment, and refresh troubleshooting.

• Strong written and verbal English communication skills, with experience interfacing directly with U.S. executives to translate complex technical findings into clear business context.

Preferred:

• Background analyzing operational data from systems such as CRMs (e.g., HubSpot), ATS/HRIS platforms, time-tracking software, or ERP systems.

• Experience in professional services, outsourcing (BPO), staffing, healthcare management, or resource-driven service industries.

• Exposure to modern cloud data warehouses like Snowflake or AWS environments (S3, RDS, Lambda).

• Familiarity with light scripting using Python for automation, data cleaning, or API processing.

• Relevant industry credentials (e.g., Microsoft PL-300) are a plus, though practical expertise is prioritized.