Data Engineering Expert – Financial Data Pipeline Development

About the Role

We’re looking for a  Data Engineering Expert  to design and build a  financial data pipeline  that connects  SAP BW  and  SAP BFC  to our  Azure Data Platform .

This role is crucial in enabling seamless integration and real-time flow of financial data, which will later power  AI-driven predictive models  for company KPI forecasting.

If you have hands-on experience in  Azure Functions, Kafka, MS Fabric , and deep knowledge of  SAP financial systems , this is your chance to shape a high-impact project that merges  finance, data engineering, and AI innovation .

Your Mission

You’ll lead the development of an end-to-end  financial data pipeline  — from data ingestion to analytics readiness — ensuring scalability, accuracy, and security across all stages.

Key Responsibilities

Design & Build Pipelines :  Develop robust and secure data pipelines between  SAP BW ,  SAP BFC , and  Azure Data Platform .

Data Integration :  Streamline data ingestion from SAP systems to Azure using  Azure Functions ,  Kafka , and  MS Fabric .

Optimize Performance :  Ensure efficient, real-time data processing for financial reporting and analytics.

Enable AI Insights :  Structure and prepare data for consumption by  AI models  to predict company KPIs.

Documentation & Support :  Deliver detailed documentation, handover materials, and team training for future maintenance.

Required Skills & Expertise

Proven experience with  Azure Data Engineering  and  pipeline development .

Strong hands-on knowledge of  SAP BW  and  SAP BFC  (financial consolidation and reporting).

Proficiency in  Azure Functions ,  Apache Kafka , and  MS Fabric .

Solid understanding of  financial data structures  and  ETL processes .

Working knowledge of  Python  for data transformation and automation.

Strong understanding of  data security ,  integrity , and  governance principles .

Nice to Have

Experience integrating  financial ERP data  into  cloud-based analytics platforms .

Familiarity with  AI / ML model data preparation  or predictive analytics.

Exposure to  real-time data streaming  and event-driven architectures.