Developer, Analytics & Reporting

WHAT'S THE JOB?

Reporting to the Manager, Solutions Innovation, the Developer, Analytics & Reporting plays a central role in advancing data-driven decision‑making across the organization. This position is responsible for developing high‑quality Power BI dashboards, building Python-based data preparation and automation workflows, and supporting the creation of reliable, scalable reporting assets used by operational teams and business leaders. This role will also support Field System Management: cleaning, preparing, updating workflows, and uploading bulk operational data for new contracts and ensuring field‑system data feeds flow correctly into reporting pipelines.

Working within the Solutions Innovation function, you will collaborate closely with business units, operational teams, and iLab team members to understand reporting needs, translate them into actionable technical solutions, and ensure analytics products are accurate, timely, and easy to use. You will help streamline the flow of data from external sources, improve the visibility of operational performance, and contribute to the organization’s focus on efficiency, transparency, and continuous improvement.

This role requires strong analytical thinking, attention to detail, and the ability to work both independently and collaboratively. You will play an important part in building repeatable reporting capabilities, supporting strategic initiatives, and enhancing the overall impact of the Solutions Innovation team.

Build and Maintain Power BI Dashboards

• Develop high-quality, user‑friendly dashboards and reports that support operational and strategic decision‑making
• Translate raw external data feeds into structured, governed Power BI datasets
• Optimize data models, DAX measures, and Power Query transformations for performance and accuracy
• Implement Row-Level Security and follow internal governance practices for secure data sharing

Develop Python-Based Data Pipelines & Automation

• Create Python scripts to ingest, clean, and transform data from varied external systems (APIs, SaaS tools, flat files, SFTP, partner feeds)
• Automate recurring data refreshes and validation processes
• Build lightweight utility scripts to support teams (e.g., preprocessing, reconciliation, data quality checks)

Field System Management

• Clean, standardize, and bulk‑upload operational data (e.g., asset lists, PM schedules) during new contract onboarding
• Manage recurring data flows from field systems into reporting environments
• Perform validation, formatting checks, and reconciliations to ensure data completeness and accuracy
• Troubleshoot data‑level issues that impact reporting

Strengthen Data Quality and Reliability

• Perform validation, anomaly detection, and reconciliation for incoming datasets
• Document data sources, assumptions, business rules, and refresh schedules
• Establish repeatable processes that reduce manual intervention and improve data trust

Collaborate with Stakeholders Across the Business

• Work with operational leaders, analysts, and managers to understand their reporting needs
• Translate business requirements into structured technical solutions
• Gather feedback from users and iterate dashboards or datasets to enhance clarity and usability
• Provide light training and support for business users adopting new dashboards

Support Solutions Innovation Initiatives

• Contribute to data and analytics components of iLab initiatives and innovation pilots
• Assist in evaluating external data sources, third‑party tools, and new reporting opportunities
• Help modernize existing reporting processes or replace inefficient legacy approaches

Maintain Standards, Documentation, and Version Control

• Use Git-based workflows to track changes to Python scripts and reusable analytics assets
• Maintain documentation for dashboards, pipelines, and supporting scripts
• Follow organizational best practices for security, consistency, and maintainability

Deliver Measurable Improvements in Reporting

• Reduce manual reporting effort across teams through automation and reusable datasets
• Improve data refresh reliability and decrease dashboard load times
• Enhance overall data visibility for leaders through standardized reporting assets

They will support operations with changes to workflows also to provide our contracts with necessary delivery information within the systems database.

Do you want to mention using the enterprise tools available.