Technical Delivery Manager(Data Lakehouse )

Key Responsibilities

• Lead the design and implementation of scalable, secure, and regulatory-compliant enterprise data and analytics platforms for the banking/FSI domain.
• Define data architecture strategies leveraging Lakehouse, Data Mesh, Data Fabric, and cloud-native data and AI technologies.
• Architect and deliver data pipelines, APIs, data products, and data-serving layers for enterprise analytics.
• Lead development of BI, reporting, predictive analytics, AI/ML, and real-time analytics solutions.
• Drive AI/ML use cases including fraud detection, customer segmentation, credit scoring, risk modeling, and next-best-offer solutions.
• Establish and implement DataOps, MLOps, DevOps, security, governance, and engineering standards.
• Lead cross-functional teams of data engineers, BI developers, data scientists, and ML engineers.
• Partner with business, architecture, application, testing, and vendor teams to define requirements and deliver solutions successfully.
• Manage technical delivery, dependencies, testing, implementation, production cutover, and post-production support.
• Provide technical leadership, resolve complex design issues, manage risks, and communicate delivery status to senior stakeholders.

Key Requirements

• 10–15+ years of experience in data and analytics technology, with strong experience in banking/financial services.
• Proven experience designing and implementing enterprise Data Lakehouse platforms using Databricks, Snowflake, Cloudera, AWS, Azure, or GCP.
• Strong expertise in data engineering, data architecture, data modeling, integration, APIs, and enterprise analytics platforms.
• Hands-on experience with technologies such as Spark, Python, SQL, Kafka, Airflow, Kubernetes, and CI/CD tools.
• Strong knowledge of BI and analytics platforms such as SAS Viya, Teradata, Power BI, Qlik, Adobe, or equivalent technologies.
• Experience implementing AI/ML solutions using Python, R, TensorFlow, PyTorch, MLflow, or similar technologies.
• Strong understanding of banking domains including risk, fraud, credit, compliance, customer analytics, and regulatory requirements.
• Proven experience leading multidisciplinary technology teams and managing complex enterprise technology deliveries.
• Excellent understanding of Agile SDLC, DevOps/MLOps, data governance, security, model governance, explainability, and audit readiness.
• Bachelor’s degree in Computer Science, Engineering, or equivalent; TOGAF, DAMA/DMBOK, CDMP, Microsoft Data & AI, SAS, or equivalent certifications are preferred.