Data Engineer

Jobs for Lebanon; Greater London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading digital assets provider seeks a skilled Data Engineer to design and maintain a robust data infrastructure. You will build data pipelines and ensure data quality for both internal and external clients. The ideal candidate will have 4+ years of experience, proficiency in AWS services, ETL processes, and programming languages like Python and SQL. This role offers an exciting opportunity to work in a dynamic environment and contribute to innovative solutions in the fintech space.

Qualifications

• 4+ years experience as a Data Engineer or similar role.
• Strong background in designing and building data pipelines, ETL processes, and data warehouses.
• Hands-on experience with cloud-based data platforms and services.

Responsibilities

• Design and build data warehouse alongside the data team.
• Develop and maintain data pipelines and ETL processes.
• Provide clean and reliable data in a safe environment.

Skills

Data pipelines

ETL processes

AWS

Python

SQL

Kubernetes

Data modeling

Apache Spark

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

AWS services (S3, Redshift, Lambda, Glue)

PostgreSQL

MySQL

Job description

Company Overview

Baanx is building digital assets services for every business. Top crypto businesses partner with Baanx for 20% of the world's cryptocurrency. We provide our services in the United States and Europe to many millions of customers.

Baanx is working on Crypto-as-a-Service Digital Banking and Digital Asset Lending services for our clients. We deliver full platforms for some of the world's biggest / leading firms in the crypto space — cards, lending, remittance, wallets, exchange.

As a Senior Backend Developer, you will be responsible for the architecture and development of BAANX applications and services, and integration with 3rd party services.

Job Description

We are seeking a talented and experienced Data Engineer to join our dynamic team. As a Data Engineer, you will play a crucial role in designing, building, and maintaining our data infrastructure to support our growing business needs.

Your role will include building a new data warehouse alongside the data team, building data pipelines to provide data to both internal and external clients, and maintaining and ensuring data quality for the business.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 4+ years experience as a Data Engineer or similar role, with a strong background in designing and building data pipelines, ETL processes, and data warehouses.
• Hands‑on experience with cloud‑based data platforms and services, particularly AWS (Amazon Web Services) including but not limited to S3, Redshift, Lambda, and Glue.
• Proficiency in programming languages such as Python, SQL, and experience with data processing frameworks/libraries such as Apache Spark, Pandas, or similar.
• Experienced in managing compute workloads and scaling with tools such as Kubernetes.
• Solid understanding of database concepts, data modelling, and relational databases (e.g., PostgreSQL, MySQL).
• Strong analytical, problem‑solving, and communication skills, with the ability to work effectively in a fast‑paced and collaborative environment.
• Experience working in the fintech or financial services industry is a plus.
• Excellent communication and collaboration skills, with the ability to interact effectively with technical and non‑technical stakeholders.

Additional Information

• Design and build data warehouse alongside the data team.
• Design, develop, and maintain data pipelines and ETL processes to ingest, process, and transform large volumes of data from various sources into our data warehouse.
• Build data pipeline to third‑party reporting and automation tools.
• Work with clients to provide clean and reliable data in a safe environment.
• Build and optimize data models, schemas, and databases to support analytical and reporting requirements.
• Implement data quality checks, monitoring, and error handling mechanisms to ensure the integrity and reliability of our data.
• Collaborate with the data team and business departments to understand data requirements and deliver data solutions that meet business needs.
• Continuously optimize and improve data infrastructure, performance, and scalability to support growing data volumes and evolving business requirements.
• Stay up‑to‑date with emerging technologies and best practices in data engineering, cloud computing, and data management.