BACKEND ENGINEER
Faishal Zaka Naufal
Building workflow-driven fintech and cloud systems.
I build reliable backend services and automation platforms that turn complex business processes into measurable, scalable systems—from workflow orchestration and decision engines to cloud data pipelines.
Backend
Engineer
I’m a backend engineer with 7+ years of experience building workflow automation platforms and fintech infrastructure. Across Nikel and KoinWorks, I’ve worked on loan onboarding, BPMN-based decision flows, business-rule orchestration, alternative-data credit scoring, and AWS serverless pipelines. My focus is turning complex business processes into reliable, measurable systems.
Key Achievements
Designed and implemented BPMN-based workflow automation for borrower and loan onboarding (LOS), reducing manual intervention and improving processing efficiency
Reduced onboarding processing time by ~60–70% through automation of credit decision workflows
Built credit scoring models using alternative data, improving loan qualification and collection effectiveness
Developed low-code automation tools enabling faster iteration of business processes
Background
Before focusing on backend systems, I studied Astronomy. That research background still informs how I approach ambiguous problems: with analytical thinking, curiosity, and care for evidence.
Target roles
- Backend Engineer
- Platform Engineer
- Workflow Automation Engineer
- Fintech Backend Engineer
- Backend Engineer — Decisioning and Data Systems
Open to backend and platform opportunities in Germany.
At a glance
Years building backend systems
Onboarding time reduced
Application lanes supported
Where I've
worked
Backend Engineer
PT. Impact Credit Solutions (Nikel)
- Designed and implemented workflow-driven borrower and loan onboarding processes using BPMN and SpiffWorkflow, reducing processing time by approximately 60–70%.
- Built and integrated Python backend services with Django and FastAPI to support workflow execution and business-rule orchestration.
- Developed a configurable automation engine with Python and Dramatiq, enabling non-engineering teams to configure and iterate on business workflows faster.
Backend Engineer | Innovation - Strategy
PT. Sejahtera Lunaria Annua (KoinWorks)
- Built fintech products and backend services to support new business opportunities and improve lending operations using Python, Node.js, and Golang.
- Developed credit scoring models (XGBoost) using alternative data (ecommerce), improving loan qualification and collection effectiveness.
- Designed data pipelines using AWS Lambda and Step Functions to process rejected loan users and generate alternative loan offerings.
Back End Developer
PT. Fairtech Digital Indonesia
- Utilized Grails Framework for web applications and ElasticSearch to enhance search capabilities.
- Contributed to major web projects including Canon Asia, Michelin Guide, and Hong Kong Tourism Board.
Tools I
use daily
Backend
Data and APIs
Workflow and Automation
Cloud and Processing
Applied ML
Systems built
around workflows
Sanitized case studies from backend, workflow automation, and fintech decisioning work. They describe the engineering problems and outcomes without exposing confidential implementation details.
Case study 01
Workflow-Driven Loan Onboarding
A generalized case study of BPMN-based borrower and loan onboarding automation.
Reduced onboarding processing time by approximately 60–70%.
Problem
Loan onboarding involved complex, changing business decisions that were difficult to execute consistently and efficiently.
My contribution
Built backend services around workflow execution and business-rule orchestration for borrower and loan onboarding.
Technical approach
Used BPMN and SpiffWorkflow to model process steps and connect them to Python, Django, and FastAPI services.
Result
Reduced onboarding processing time by approximately 60–70%.
Case study 02
Workflow Automation Engine
A configurable automation engine for iterating on business processes with less engineering friction.
Created a reusable way to automate business processes while keeping workflow configuration closer to the teams that operate them.
Problem
Business workflows needed to change quickly, while every process adjustment could otherwise require a fully bespoke engineering cycle.
My contribution
Developed the engine and the backend execution path that allowed non-engineering teams to configure and iterate on workflows faster.
Technical approach
Combined configurable workflow definitions with Python execution and Dramatiq for background processing.
Result
Created a reusable way to automate business processes while keeping workflow configuration closer to the teams that operate them.
Case study 03
Alternative Credit Decisioning Pipeline
A generalized fintech case study combining alternative data, scoring, and serverless processing.
Supported alternative loan offerings and lending decisions through reusable scoring and pipeline workflows.
Problem
Lending operations needed additional signals and processing paths to support loan qualification and collection effectiveness.
My contribution
Built backend and data-pipeline components for alternative-data processing and credit decisioning.
Technical approach
Used XGBoost for credit scoring and AWS Lambda with Step Functions for serverless data processing pipelines.
Result
Supported alternative loan offerings and lending decisions through reusable scoring and pipeline workflows.
Research and Earlier Work
Research and earlier software work that supports the wider engineering picture without competing with the backend case studies.
Astronomical Image Denoising
Designed a novelty ML model using CycleGAN with attention layers to enhance astronomical images.
Read related writing →COVID-19 Data Modeling
Analyzed community mobility and weather variability using Random Forest and XGBoost.
Social Media Automation
Developed sentiment analysis tools and social media automation using Python and ADB.
Let’s
connect
I’m open to backend, platform, and workflow automation opportunities in Germany.