Senior Finance Data Engineer

About the role

We're looking for a Senior Data Engineer to join our Finance BI team and help shape the future of data-driven decision making across IFS. In this role, you'll design, build, and operate trusted finance data products and scalable data pipelines that power financial reporting, forecasting, planning, ARR analytics, executive dashboards, and emerging AI-driven insights.

Responsibilities

• Design, build, test, and maintain scalable data pipelines across finance and enterprise source systems.
• Develop and optimize ELT/ETL processes using modern cloud data platforms and engineering best practices.
• Create curated, analytics-ready datasets and data models for Power BI, forecasting, planning, and executive reporting.
• Implement data quality frameworks, reconciliation processes, validation controls, and monitoring capabilities to ensure trust in reporting outputs.
• Support strategic Finance BI initiatives, including ARR by Product reporting, personnel planning, finance dashboards, forecasting solutions, and other reporting programs.
• Partner with analysts and business stakeholders to understand reporting requirements, metric definitions, and analytical use cases.
• Optimize the performance, reliability, scalability, and usability of datasets, semantic models, and analytics pipelines.
• Apply data security, governance, access management, and documentation standards aligned with enterprise best practices.
• Contribute to DevOps, CI/CD, testing, deployment, and release management processes.
• Support AI, Copilot, and agent-based analytics solutions through well-governed, reusable, and trusted data assets.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Finance Technology, or a related field, or equivalent practical experience.
• Typically 5+ years of experience in data engineering, analytics engineering, business intelligence, or data platform delivery.
• Strong hands-on experience designing and building enterprise data engineering solutions.
• Advanced SQL skills and experience working with complex financial, operational, or business-critical datasets.
• Strong Python experience for data transformation, automation, orchestration, and pipeline development.
• Experience building and supporting production-grade data pipelines on Microsoft Fabric, Azure Data Platform, Databricks, Snowflake, or comparable cloud data platforms.
• Solid understanding of dimensional modeling, semantic layers, data governance, lineage, data quality frameworks, and production support practices.
• Experience supporting Power BI datasets, semantic models, or enterprise reporting environments.
• Ability to translate business requirements into scalable and maintainable data solutions.
• Strong analytical thinking, problem-solving, documentation, and stakeholder communication skills.

Preferred Qualifications

• Experience with Spark, PySpark, Delta Lake, lakehouse architectures, or medallion data design patterns.
• Experience working with Finance, FP&A, SaaS metrics, ARR reporting, ERP systems, or planning and forecasting data.
• Hands-on experience with Azure DevOps, Git, CI/CD pipelines, and modern software engineering practices.
• Exposure to AI-enabled analytics, Microsoft Copilot, semantic model optimization, or data agents.
• Understanding of data privacy, financial controls, risk management, and governance requirements in enterprise environments.