Collaborate with business stakeholders and cross-functional teams to gather and analyze business requirements.
Participate in designing high-level and detailed solutions to address business problems in collaboration with the project team.
Contribute to the end-to-end model development lifecycle, including data cleaning, data analysis, model building, model testing, collecting business feedback, model deployment, data visualization, model maintenance, and knowledge transfer to business users and project teams.
Our key skills
Spark ETL
Python
Oracle
Job Requirements
Bachelor’s degree in Information Technology, Telecommunications, Finance, Banking, Economics, or a related field.
Graduated with distinction or obtained a degree from an overseas university is an advantage.
Professional certifications in Data Engineering (DE), Data Science (DS), or Data Analytics (DA) are preferred.
At least 2 years of hands-on experience in software development, data engineering, data science, data analytics, or related technology projects.
Solid understanding of Hadoop ecosystem architecture, including physical and logical architecture, as well as core components such as the Ingestion, Processing, and Consumption layers.
Fundamental knowledge of Data Mining and Machine Learning.
Hands-on experience with Spark ETL using Scala and Python within the Hadoop ecosystem.
Experience optimizing data processing pipelines, including Landing Zone, Working Zone, Gold Zone, large-scale job design, and workflow orchestration techniques.
Experience with at least one SQL database, such as Oracle, Netezza, MySQL, PostgreSQL, MariaDB, or Amazon Aurora.
Experience with at least one NoSQL database, such as Elasticsearch, Apache Cassandra, Apache HBase, Google Bigtable, or Apache Pinot.
Experience with at least one Graph or In-Memory database, such as Neo4j, TigerGraph, Amazon Neptune, Redis, or Memcached.
Hands-on experience with Machine Learning frameworks and tools, including Keras, TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas, Apache Zeppelin, JupyterHub, and Visual Studio Code.
Experience developing applications using Flask, FastAPI, and Gunicorn.
Experience using data visualization and business intelligence tools such as Tableau and Power BI.
Knowledge of Unit Testing, Integration Testing, Functional Testing, A/B Testing, and Cross-Validation techniques.
Experience working on banking projects, such as Mobile Banking applications or T24 Core Banking, is highly preferred.
Experience working in Agile development environments.
Previous experience in the banking or financial services industry is an advantage.
Basic English reading and writing skills are required; listening and speaking skills are a plus. Candidates holding internationally recognized English certifications are preferred.
