Evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking of an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and work-flows. Coordinates and contribute to the objectives of data science initiatives and overall business through leveraging in-depth understanding of how areas collectively integrate within the sub-function. Assumes informal/formal leadership role through coaching and training of new recruits. Significantly influences decisions, work, and performance of all teams through advice, counsel and/or facilitating services to others in the business. Conducts strategic data analysis, identifies insights and implications and make strategic recommendations, develops data displays that clearly communicate complex analysis. Mines and analyzes data from various banking platforms to drive optimization and improve data quality. Delivers analytics initiatives to address business problems with the ability to identify data required, assess time & effort required and establish a project plan. Consults with business clients to identify system functional specifications. Applies comprehensive understanding of how multiple areas collectively integrate to contribute towards achieving business goals. Consults with users and clients to solve complex system issues/problems through in-depth evaluation of business processes, systems and industry standards; recommends solutions. Leads system change process from requirements through implementation; provides user and operational support of application to business users Formulate and define systems scope and objectives for complex projects through research and fact-finding combined with an understanding of applicable business systems and industry standards. Impacts the business directly by ensuring the quality of work provided by self and others; impacts own team and closely related work teams. Considers the business implications of the application of technology to the current business environment; identifies and communicates risks and impacts. Drives communication between business leaders and IT; exhibits sound and comprehensive communication and diplomacy skills to exchange complex information. Involved in coaching and training of new recruits. Significant impact in terms of project size, geography, etc. by influencing decisions through advice, counsel and/or facilitating services to others in area of specialization. Work and performance of all teams in the area are directly affected by the performance of the individual. 8+ years experience using tools for statistical modeling of large data sets Database Development & Architecture: Design, develop, and maintain complex database solutions across MongoDB, Oracle, and other SQL databases. Create optimal data models, schemas, and stored procedures to support high-throughput applications. Data Pipeline Construction: Build and manage resilient, scalable ETL/ELT pipelines using Python to process and integrate large volumes of data from diverse source systems into our core data platforms. Big Data Engineering: Engineer and implement solutions within our Big Data ecosystem (e.g., Hadoop, Spark, Hive, Kafka) to handle large-scale data processing, batch analytics, and real-time data streams. Python Development: Write high-quality, production-ready Python code for data manipulation, API development, and automation. Utilize a range of libraries and frameworks relevant to data engineering (e.g., Pandas, PySpark, SQLAlchemy, PyMongo). Performance Optimization: Proactively monitor, troubleshoot, and optimize the performance of our databases and data pipelines. Focus on query tuning, indexing strategies, and resource management to ensure low-latency data access. Data Quality and Integrity: Implement data quality checks, validation rules, and monitoring frameworks within the data pipelines to ensure the accuracy, consistency, and reliability of our KYC data. Collaboration: Work closely with application developers, data scientists, and data analysts to understand their data requirements and provide robust, well-documented data solutions and services. Technical Leadership: Provide subject matter expertise on database and data engineering best practices. Mentor junior engineers and contribute to a culture of technical excellence. Bachelor's/University degree or equivalent experience ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------