Senior Data Engineer (Remote)

Aajil; Riyadh; Hybrid; SAR 299,000 - 450,000; Full time

Job summary

A leading fintech company in Riyadh seeks a Senior Data Engineer to tackle complex data engineering challenges that drive real-time credit decisions. You will be responsible for building and scaling the data infrastructure while collaborating with diverse teams to produce effective solutions. The ideal candidate has over 5 years of experience in data engineering, deep expertise in cloud platforms like GCP or AWS, and strong Python programming skills. This role offers a unique opportunity to make a real impact in the fintech sector.

Benefits

Collaborative team environment

Cutting-edge technology stack

Opportunities for real impact

Qualifications

• 5+ years of experience in data engineering with production data systems.
• Deep expertise in cloud platforms and modern data tools.
• Strong programming fundamentals in Python.

Responsibilities

• Build and scale data infrastructure for credit decisions.
• Design and implement data pipelines using GCP or AWS.
• Optimize ETL/ELT workflows for data performance.

Skills

Data engineering

Cloud platforms (GCP/AWS)

Python programming

Data architecture

Performance optimization

ETL/ELT workflows

Machine learning models

Collaboration skills

Problem-solving

Tools

Kafka

Airflow

dbt

Spark

BigQuery/Redshift

Job description

At Aajil (formerly Buildnow), we're powering smarter decisions for B2B commerce through data-driven credit solutions. As a Senior Data Engineer (Remote), you'll build and scale the data infrastructure that fuels our underwriting models, analytics dashboards, and real-time decision engines. If you have serious technical chops, love designing robust systems at scale, and thrive in collaborative environments, this is your opportunity to do some of the most challenging data engineering work in fintech.

What You'll Do

You'll tackle complex data engineering challenges and build production systems that process high-volume transactional data. Your responsibilities include:

• Building and scaling data infrastructure that processes millions in transaction volume and powers real-time credit decisions.
• Designing and implementing data pipelines across data lakehouses, OLAP systems, and event-driven architectures using GCP or AWS.
• Optimizing ETL/ELT workflows with tools like dbt, Airflow, Spark, and Kafka to ensure data reliability and performance at scale.
• Implementing real-time data processing and streaming analytics that support instant underwriting decisions.
• Productionizing ML models in collaboration with data scientists, ensuring models run efficiently in production.
• Contributing to technical strategy for data architecture, tooling decisions, and infrastructure improvements.
• Collaborating closely with engineering leadership, Risk, Product, and Analytics teams to solve complex data challenges.
• Writing production-grade code with strong Python fundamentals, clean architecture, and robust testing.
• Ensuring data quality, governance, and security across all systems and pipelines.

What We're Looking For

We need someone with serious technical depth who can hit the ground running and tackle our hardest data problems. The ideal candidate will have:

• 5+ years of experience in data engineering with a proven track record of building and scaling production data systems in high-growth environments.
• Deep expertise in cloud platforms (GCP/AWS) and modern data tools (dbt, Airflow, Spark, Kafka, BigQuery/Redshift).
• Strong programming fundamentals in Python, with solid understanding of data structures, algorithms, and software engineering best practices.
• Hands-on experience with diverse data architectures, including data lakehouses (Delta Lake, Iceberg), OLAP systems, and event-driven pipelines.
• Proven ability to design and optimize for scale, tackling performance, cost, and reliability challenges in high-throughput environments.
• Experience productionizing ML models and working closely with data science teams.
• Strong problem-solving skills and ability to troubleshoot complex issues across distributed systems.
• Excellent collaboration skills and ability to work effectively with both technical and non-technical stakeholders.
• Track record of shipping complex projects from design to production.

Nice-to-Have:

• Experience in fintech, lending, or credit risk environments.
• Familiarity with data governance and compliance frameworks.
• Contributions to open-source data tools or active involvement in the data engineering community.
• Experience with real-time fraud detection or underwriting systems.

Why Aajil?

• Hard Problems: Tackle challenging data engineering problems in credit risk, fraud detection, and real-time underwriting.
• Cutting-Edge Stack: Work with modern tools like Kafka, Airflow, dbt, Delta Lake, and cloud-native architectures.
• Collaborative Team: Work alongside experienced engineers solving complex problems together.
• Real Impact: Your work directly influences how we underwrite 800+ SMEs and process millions in transaction volume.
• Builder Culture: No bureaucracy, just meaningful technical work that moves the business forward.