Responsibilities:

📍Build a scalable and reliable data infrastructure from scratch and gradually form a Data Engineering team. 📍Implement real-time data streaming (CDC) and apply a Data Mesh approach for secure, segmented data management. 📍Establish data governance standards and create a unified data repository for analytics, AI/ML, and reporting. 📍Develop reporting systems, dashboards, and visualizations for actionable business insights based on both technical and non-technical requests. 📍Set up effective workflows between the analytics team and business units, ensuring smooth collaboration and data-driven decision-making. 📍Ensure data security and compliance with industry regulations (e.g., GDPR, PCI-DSS, SOC 2) through encryption, access control, and data masking. 📍Oversee automated monitoring, anomaly detection, and data integrity tracking to prevent security incidents. 📍Build an AI/ML-ready data ecosystem to support predictive analytics, fraud detection, and financial risk assessment.

Requirements:

📍8+ years of experience in Data Engineering. 📍2+ years of leadership experience (team management, process development). 📍Experience in building data architecture and implementing solutions from scratch 📍Strong knowledge of ETL/ELT processes, data warehouse (DWH) development, and working with OLTP and OLAP systems. 📍Experience with cloud platforms (AWS, GCP, or Azure). 📍Understanding of data security principles and experience implementing role-based access control (RBAC). 📍Experience working with BI tools and setting up advanced reporting. 📍Experience implementing and using AI/ML for predictive analytics (a plus). 📍Experience in fintech (preferred, but not required).

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