Technical Delivery Manager

Experience: 10+ Years
Role: Technical Delivery Manager

Key Skills:
- 10-15years of experience of implementing a Data Lakehouse preferably in FSI domain (usingplatforms such as Databricks, Snowflake, Cloudera, Huawei, Alibaba, GoogleCloud, AWS, Azure),

- BI &Analytics Platforms: SAS Viya, Teradata, Adobe, Cloudera, Microsoft Power BI /Azure Analytics, Qlik.

- AI/ML,Analytics: Spark Scala, Python, R, Java, TensorFlow, PyTorch, Data Ops tooling,MLflow, Kubernetes

- Streaming& Integration: Kafka, Spark Streaming, Informatica, Talend.

- Databases,Data federation: SQL, NoSQL DBs, Denodo, Snowflake

- Cloud &DevOps: Kubernetes, Airflow, GitOps, CI/CD tools

- Knowledge ofstatistical modeling, predictive analytics, NLP, and AI-driven decisionsystems.

- Financialservices data models & data modelling tools and data governance processes

- Hadooplanguages & tools – Spark, Python, R, Pig, Hue, Impala, Hive, Hbase,Informatica IDL

- Platformssuch as Kubernetes or OpenShift for deploying container-based workload

- Experience with AI in banking regulatory contexts(model governance, explainability, audit readiness).

- Exposure to data mesh, federated governance, andadvanced BI/AI architectures.

- 10+ years in data/analytics technology, with 5+ yearsin a technology delivery role.

- Demonstrated ability to lead multi-disciplinary teams(engineering, BI, data science).

- Strong grasp of banking operations, risk, compliance,fraud, and customer analytics.

- Excellent communication skills to influence C-levelexecutives and business stakeholders.

Responsibilities:

We are seeking an experienced senior Technology Leader to design, build, and manage data and analytics solutions for the banking domain. This role spans data architecture, analytics application development, and AI/ML application integration — ensuring scalable, secure, and regulatory-compliant platforms that deliver business value. The ideal candidate combines deep technical expertise in data engineering and analytics platforms with the ability to lead teams and partner with business stakeholders.

Architecture & Strategy

- Contribute to enterprise data architecture strategy and regulatory needs.

- Work on end-to-end data platforms supporting traditional BI, advanced analytics, AI/ML, and real-time insights.

- Define data analytics solution adapting concepts like Lakehouse, Data Mesh, Data Fabric while adopting cloud-native data & AI services and modern integration patterns.

- Work on banking-grade platforms including Opensource technologies, Teradata, Cloudera, SAS Viya, Adobe, IBM DataPack, Microsoft Power BI and other enterprise data analytics tools.

Solution Design & Delivery

- Build and maintain enterprise data platforms leveraging open-source technologies ranging data integration, data base, visualisation, modelling, apis/micro services

- Lead design and delivery of analytical applications leveraging enterprise Data Analytics platforms (dashboards, predictive models, reporting suites, self-service and operational analytics)

- Build and operationalize Data products, AI/ML solutions for banking use cases such as next best offer, fraud detection, customer segmentation, credit scoring, and risk modelling etc.

- Architect and develop data pipelines, APIs, and data serving layers for production-grade analytics.

- Deploy best practices in Data Ops, ML Ops and integration with regulatory-compliant systems.

- Define enterprise design principles, security and control standards

Team & Leadership

- Plan technical deliverables (including any system enhancements and upgrades) to meet project’s requirements within allocated budget and schedule.

- Plan & collaborate across different application teams to manage technical dependencies of the solution

- Provide status update related to technical delivery to Project Manager (PM)

- Partner with System Analysts and Business Solution Specialist to collate, understand and finalize functional and technical requirements

- Partner with test Manager for delivery through SIT, UAT , performance / load testing and application security testing with quality results

- Manage technical implementation plan across application teams - coordinate technical implementation activities across application teams to ensure non-event production cutover and adequate post implementation support

- Escalate issues that impacts project schedule on timely basis and propose workarounds/resolutions

- Lead and mentor cross-functional teams of data engineers, BI developers, data scientists, and ML engineers.

- Establish engineering standards, DevOps/MLOps pipelines, and governance for data analytics applications

- Collaborate closely with business leaders, ensuring technical solutions meet business goals and compliance standards.

Requirements:

Education:

- Bachelor’s degree/University degree in Computer Science, Engineering, or equivalent experience

Certifications:

- TOGAF, DAMA/DMBOK, CDMP, SAS Certified AI/ML Specialist, Microsoft Data & AI, or equivalent.

What will help you succeed in this role:

- Adopt an uncompromising attitude when it comes to quality and help raise bar of products and team members

- Be a team player who communicates effectively and professionally with both internal and external customers

- Identify ideas to improve system performance and impact availability

- Embrace tackling and resolving complex technical design issues

- Possess strong problem solving and decision-making skills while exercising good judgment

- Strong analytical and problem-solving skills

- Ability to work on multiple projects at a time

- Be able to work under pressure and manage deadlines or unexpected changes in expectations or requirements

- Good communication skills - ability to convey technical information to non-technical audience

- Ability to understand the big picture

- Ability to develop long lasting relationships with all levels

- Deep understanding and experience in software development cycle, including Agile based rapid delivery

- Collaborate with business and IT to analyse, elicit and review business requirements

- Facilitate communication between vendor, project team, business stakeholders and internal IT team

- Ability to work in a team distributed across multiple locations