Technical Delivery Manager(Data Lakehouse )

optimum solutions (singapore) pte ltd; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Optimum Solutions (Singapore) Pte Ltd is seeking a senior leader to design and implement scalable, secure enterprise data and analytics platforms for the banking/FSI sector in Singapore.

The role focuses on defining data architecture strategies, building data pipelines, APIs, and data-serving layers while driving BI, AI/ML, and real-time analytics. You will lead cross-functional teams and collaborate with business, architecture, testing, and vendor groups to deliver compliant solutions.

Qualifications

• Experience designing and implementing enterprise data platforms.
• Hands-on with data engineering, data architecture, and APIs.
• Strong knowledge of data governance, security, and compliance in banking/FSI.

Responsibilities

• Lead 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, DataFabric, and cloud-native data and AI technologies.
• Architect and deliver datapipelines, APIs, dataproducts, 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 deliversolutions 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.

Skills

Data engineering

Data architecture

APIs

Spark

Python

SQL

Kafka

Airflow

Kubernetes

CI/CD

BI tools

AI/ML

Regulatory knowledge

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Snowflake

Cloudera

AWS

Azure

GCP

Job description

KeyResponsibilities

1. Lead the designand implementation ofscalable, secure, andregulatory-compliant enterprisedata and analyticsplatforms for thebanking/FSI domain.
2. Define data architecturestrategies leveraging Lakehouse, Data Mesh, DataFabric, and cloud-native data andAI technologies.
3. Architectand deliver datapipelines, APIs, dataproducts, and data-serving layers forenterprise analytics.
4. Leaddevelopment of BI, reporting, predictiveanalytics, AI/ML, and real-timeanalytics solutions.
5. Drive AI/MLuse cases includingfraud detection, customersegmentation, credit scoring, riskmodeling, and next-best-offer solutions.
6. Establish and implementDataOps, MLOps, DevOps, security, governance,and engineering standards.
7. Lead cross-functionalteams of dataengineers, BI developers, data scientists, andML engineers.
8. Partner with business, architecture, application,testing, and vendorteams to definerequirements and deliversolutions successfully.
9. Manage technical delivery, dependencies, testing,implementation, productioncutover, and post-production support.
10. Provide technical leadership, resolve complex designissues, manage risks, and communicate deliverystatus to seniorstakeholders.

Key Requirements

1. 10-15+years of experiencein data andanalytics technology, withstrong experience inbanking/financial services.
2. Proven experience designingand implementing enterpriseData Lakehouse platformsusing Databricks, Snowflake, Cloudera,AWS, Azure, orGCP.
3. Strong expertise indata engineering, dataarchitecture, data modeling, integration, APIs, andenterprise analytics platforms.
4. Hands-onexperience with technologiessuch as Spark, Python, SQL, Kafka, Airflow, Kubernetes, andCI/CD tools.
5. Strong knowledge ofBI and analyticsplatforms suchas SAS Viya, Teradata, Power BI, Qlik, Adobe, orequivalent technologies.
6. Experience implementingAI/ML solutionsusing Python, R,TensorFlow, PyTorch, MLflow, or similar technologies.
7. Strong understandingof banking domains includingrisk, fraud, credit, compliance, customeranalytics, and regulatoryrequirements.
8. Proven experience leadingmultidisciplinary technology teams and managingcomplex enterprise technologydeliveries.
9. Excellent understandingof Agile SDLC, DevOps/MLOps, datagovernance, security, modelgovernance, explainability, and audit readiness.
10. Bachelor's degree inComputer Science,Engineering, or equivalent; TOGAF, DAMA/DMBOK, CDMP, Microsoft Data& AI, SAS, orequivalent certificationsare preferred.