Mid-level Data Engineer – FinTech

About the role

We are seeking a versatile Data Engineer who can operate across data engineering, analytics, and data science within a fintech environment. The ideal candidate will build scalable pipelines, derive business insights, and develop machine‑learning models that drive real‑world financial applications.

Key responsibilities

• Design, develop, and optimise scalable data pipelines and ETL/ELT processes.
• Work with data warehouse and lakehouse architectures, handling large structured and unstructured datasets.
• Conduct data analysis to uncover customer behaviour, transaction patterns, and business trends.
• Create dashboards, KPIs, and BI reports for management‑level insights.
• Build, deploy, and monitor predictive and machine‑learning models for customer segmentation, recommendations, and personalization.

Required profile

• Bachelor’s degree in Computer Engineering, Computer Science, Data Science, Statistics, Mathematics, or a related discipline.
• 3–5 years of experience in data engineering, analytics, data science, or big‑data environments.
• Graduates from TU, KU, or other recognised universities are encouraged to apply.

Required skills

• Strong proficiency in Python (Pandas, NumPy, Scikit‑learn).
• Working knowledge of Scala and Java.
• Advanced SQL and database management.
• Hands‑on experience with Apache Spark / PySpark.
• Familiarity with Hadoop/HDFS, Apache Airflow, Apache Kafka, Apache Iceberg, and Data Lakehouse technologies.