Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.

Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.

Role Overview

We are seeking a Senior Data Engineer to design, develop, and maintain the data infrastructure that supports the organization's AI, machine learning, and analytics initiatives. Working closely with data scientists, ML engineers, and business stakeholders, the Senior Data Engineer will be responsible for building scalable, reliable data pipelines and ensuring data is accessible, consistent, and production-ready across the organization.

Key Responsibilities

Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics

Work closely with data scientists, ML engineers, and stakeholders to ensure data is accessible, consistent, and reliable for ongoing projects

Develop and maintain APIs for data access and manipulation, and integrate with external data services as needed

Manage and optimize data storage solutions for both structured and unstructured data, including relational databases, NoSQL databases, search engines such as Elasticsearch, and object storage, covering text, image, audio, and video data to support machine learning model requirements

Implement data quality monitoring processes to ensure production data is always accurate and available to key stakeholders

Collaborate with ML engineers on data-related technical issues and provide architectural guidance and solutions

Support metadata management and data governance using cataloging tools such as OpenMetadata

Ensure compliance with data security and privacy policies across all data systems

Maintain clear and up-to-date documentation including data dictionaries, metadata, and architectural diagrams

Contribute to real-time and streaming data processing requirements where applicable

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience

8 or more years of experience in a data engineering role

Proficiency in Python, Java, and Scala, with experience managing large-scale data at terabyte to petabyte scale

Hands-on experience with big data technologies including Hadoop, Spark, and Flink

Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar

Strong understanding of data warehousing, ETL processes, and data modeling concepts

Experience with cloud platforms, with AWS as the primary platform including S3, Redshift, Glue, and Lambda; Azure, GCP, and VMware experience is beneficial

Experience with API development using RESTful or GraphQL approaches

Knowledge of DevOps practices, CI/CD, and containerization using Docker or Kubernetes

Familiarity with BI tools such as Metabase and data catalog tooling such as OpenMetadata

Experience with streaming platforms such as Kafka or RabbitMQ

Fintech sector experience is an advantage

Technical Skills

Languages: Python, Java, Scala, SQL, Bash

Big Data: Hadoop, Spark, Flink

Unstructured Data: Text, Image, Audio and Video

Databases: MySQL, PostgreSQL, MongoDB, Cassandra, HBase, Redis

Cloud: AWS (S3, Redshift, Glue, Lambda) as primary; Azure, GCP, VMware

APIs: RESTful, GraphQL, OpenAPI

Data Services: Kafka, RabbitMQ

Containers: Docker, Kubernetes

BI and Cataloging: Metabase, OpenMetadata

Why Join Us?

Work with one of the world’s leading financial derivatives institutions.