About the Role
Our company operates in the energy domain, processing large volumes of utility bill data (primarily PDFs) to identify and recover overcharged payments. This role is critical in transforming raw, unstructured data into reliable, scalable, and actionable datasets that power analytics, operations, and future AI initiatives.
You will work closely with leadership and cross‑functional teams to design data models, build pipelines, and enable data-driven decision‑making across the organization.
What You’ll Do
* Design, build, and maintain scalable data pipelines (ETL/ELT) to process structured and unstructured data (including PDF-based data extraction workflows).
* Model and transform data into clean, reliable datasets optimized for analytics and business intelligence.
* Ensure data quality, consistency, and availability across systems.
* Partner with business and executive teams to understand data needs and enable data‑driven decision‑making.
* Develop and maintain dashboards and reports using tools like Power BI.
* Automate data workflows and reporting processes to improve efficiency and scalability.
* Collaborate with backend and engineering teams to integrate data systems and APIs.
* Contribute to the definition of data architecture and best practices.
* Support exploratory analysis and provide high-quality datasets for analytics and future machine learning use cases.
* Communicate technical concepts and data insights clearly to both technical and non‑technical stakeholders.
What Your Day Might Look Like
* Building pipelines to extract and structure data from energy bills.
* Designing data models in PostgreSQL for analytics consumption.
* Creating reliable datasets to support financial recovery analysis.
* Developing dashboards to track recovered amounts, anomalies, and operational KPIs.
* Working with leadership to prioritize high-impact data initiatives.
* Improving data reliability and reducing manual processes through automation.
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