Our client is a leading bank and financial services group who we are supporting with their innovation and machine learning agenda with the addition of Lead Data Engineer focusing on data analytics to drive business activities. They have had extensive success in the last few years and expanding their current division to cover the wider functions.
Job Responsibilities:
- Serve as the primary contact within the Data & Analytics department for all banking data requests from our Data Scientist team and top-level business stakeholders.
- Manage the design of AI and analytics-focused data models, and oversee the data transformation program with assistance from our data engineering team.
- Spearhead the DataOps transformation to facilitate self-service, high-efficiency data ETL for both ad-hoc analysis and real-time large-scale Machine Learning/AI model inference.
- Actively engage in data ETL pipeline development, carrying out data quality checks, and conducting peer coding reviews.
- Facilitate cross-market data design communication to leverage data synergies.
- Lead and help with data analysis and the extraction of business insights.
Job Requirements:
- 5+ years experience in data-related roles within a Financial Institute, preferably in banking.
- Advanced skills in SQL, Python, PostgreSQL, optional Spark, and Cloud-native data pipeline automation tools such as BigQuery.
- Proven success in executing large-scale data projects or products.
- Prior experience in designing and developing solutions for high-volume real-time data processing, storage, and manipulation.
- Thorough understanding of DevOps, DataOps or MLOps.
- Experience in Cloud-native data ETL development is a plus.
