Data Engineer (Finance & Analytics)

We are looking for a Finance Database Engineer to join our growing team. This role sits at the intersection of finance, technology, and engineering, and will be responsible for building and maintaining scalable data solutions that support financial reporting and operational decision-making. This is a hands-on role with significant ownership, where you will work closely with finance and operations teams to improve data visibility, accuracy, and efficiency across the organization. Primary Responsibilities: Design, build, and maintain data pipelines and applications using Microsoft Azure and Microsoft Fabric Develop and optimize SQL data models to support financial reporting and analysis Build and maintain Power BI dashboards and reporting solutions for business stakeholders Ensure data accuracy and integrity through validation, reconciliation, and issue investigation Own end-to-end data workflows, from ingestion through transformation and reporting Collaborate with finance and operations teams to translate business needs into scalable data solutions Identify opportunities to improve data processes, automation, and system performance Work closely with IT teams to ensure security, governance, and compliance of financial data. Optimize SQL queries and improve report performance. Focuses on transforming raw data into reliable reporting models. Requirements Bachelor’s degree in computer science, Computer Engineering, Information Systems, or a related field. 3+ years of experience in data engineering, analytics engineering, or software engineering with financial order Information DP-700 Certification (Preferred) Technical Requirements Experience with Microsoft Azure. Hands-on experience with Microsoft Fabric (Lakehouse, Data Warehouse, Data Factory). Experience with Power Query, DAX, and SQL with large, complex datasets. Familiarity with Git and/or Azure DevOps for version control. Knowledge of Python for data processing and automation (preferred). Experience integrating data through APIs or external data sources. Understanding of data warehousing concepts and dimensional modeling. Ability to work in mixed time zones with various teams including Pacific Standard (USA) Experience building reports and data models in Power BI Strong understanding of ETL/ELT pipelines and data validation processes Experience working with financial or operational data is a strong plus Soft skills requirements: Strong analytical and problem-solving skills. Ability to communicate technical concepts to non-technical stakeholders. Excellent stakeholder management and collaboration skills. Strong organizational and time management skills. Continuous improvement mindset with a proactive approach to automation and process optimization.