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.