Data Engineer
Summary
Senior Data Engineer builds and scales reliable ETL/ELT pipelines, data ingestion systems, and cloud data warehouses in AWS to power analytics and AI workflows using Python, SQL, and modern data stack.
About Finkraft
Finkraft is a fast-growing fintech startup building infrastructure to simplify and modernize financial operations. Data is central to everything we do — powering analytics, automation, and AI-driven products.
Role Overview
We’re looking for a Senior Data Engineer to build and scale reliable data systems that power analytics and AI. You’ll own data pipelines end-to-end and enable high-quality, production-grade data across the organization.
What You’ll Do
Build and maintain scalable ETL/ELT pipelines (batch & near real-time) using python
Design data ingestion systems across multiple sources
Optimize data storage and performance on cloud (AWS) data warehouses
Implement data quality checks, validation, and monitoring (SLAs)
Define data models and contracts across systems
Enable analytics and AI/ML workflows (feature stores, pipelines)
Collaborate with product, analytics, and engineering teams
Work with Python, PostgreSQL, and MongoDB for data processing
Deploy data pipelines on AWS infrastructure
Manage data infrastructure for microservices architecture
Requirements
What We’re Looking For
5–8 years in Data Engineering
Strong Python programming skills for data pipelines
Strong SQL and data modeling skills
Experience with modern stack (Airflow, dbt, Spark, Kafka or similar)
Experience with cloud data warehouses / lakehouse architectures
Strong ownership mindset and focus on data reliability & correctness
Good to Have
Exposure to ML/AI pipelines
Experience with large-scale or fintech datasets
Kafka (event streaming for real-time data pipelines)
Docker & Kubernetes (containerized data pipelines)
Playwright/Selenium (web scraping for data ingestion)
Benefits
Why Join Us
Build the core data backbone of a fintech platform
Direct impact on analytics, AI, and product decisions
High ownership, fast-paced environment
Work on cutting-edge data infrastructure and AI/ML workflows