VP - Data Analytics (ML, Python,Big Data)

Tangspac Consulting Group; Singapore; On-site; SGD 250,000 - 350,000; Full time

Job summary

Tangspac Consulting Group partners with a leading bank to recruit a VP of Data Analytics to drive enterprise data, analytics and AI-enabled solutions across the organization, supporting growth, regulatory compliance, risk management and customer insights.

You will lead end-to-end delivery across the SDLC, translate regulatory requirements into scalable architectures, and design modern data platforms while collaborating with cross-functional teams to ensure data quality and governance.

Qualifications

• Experience delivering large-scale data and analytics in banking/FS.
• Expertise in requirements, design, data modelling, and governance.
• Hands-on with Databricks, Snowflake, Azure Fabric, BigQuery, Hadoop, Spark.
• Proficient in SQL and Python; BI tools like Power BI or QlikSense.
• Knowledge of ML, NLP, AI governance, explainability, data lineage, and regulatory controls.
• Experience with data integration, quality, metadata, and enterprise data architecture.

Responsibilities

• Lead end-to-end delivery of enterprise data analytics across the full SDLC.
• Translate regulatory and business requirements into scalable data architectures and roadmaps.
• Design data platforms for structured, semi-structured and unstructured data.
• Collaborate with business, technology, data science, and operations teams to ensure data integrity and compliance.
• Drive governance, platform modernization, and continuous improvement initiatives.

Skills

Data analytics

SDLC

SQL

Python

Power BI

QlikSense

Databricks

Snowflake

Azure Fabric

BigQuery

Hadoop

Spark

AI governance

NLP

Regulatory compliance

Data governance

Data lineage

Data integration

Tools

Databricks

Snowflake

Azure Fabric

BigQuery

Hadoop

Spark

Job description

Join a leading bank as a VP - Data Analytics, where you will drive the delivery of enterprise data, analytics, and AI-enabled solutions that support business growth, regulatory compliance, risk management, and customer insights across the organization.

• Lead end-to-end delivery of enterprise data, analytics, and AI-enabled solutions across the full SDLC, from requirements gathering through implementation and production support.
• Analyze business and regulatory requirements and translate them into scalable data architectures, functional designs, and solution roadmaps
• Design and govern modern data platforms supporting structured, semi-structured, and unstructured data, including advanced analytics, machine learning, NLP, and real-time insights.
• Collaborate with business, technology, data science, and operations teams to ensure solution quality, data integrity, regulatory compliance, and successful delivery.
• Drive innovation, platform modernization, data governance, root cause analysis, and continuous improvement initiatives to enhance business value and operational efficiency.

Requirements

• Proven experience delivering large-scale data, analytics, and decision-support solutions within banking or financial services environments.
• Strong expertise in business analysis, requirements management, solution design, data modelling, data governance, and regulatory compliance.
• Hands‑on experience with modern data platforms such as Databricks, Snowflake, Azure Fabric, BigQuery, Hadoop, Spark, and related technologies.
• Proficiency in SQL and data analytics technologies, with working knowledge of Python and BI/visualization tools such as Power BI or QlikSense. [
• Strong understanding of machine learning, NLP, AI governance, explainability, data lineage, and regulatory controls for AI-enabled solutions.
• Experience with data integration, data quality management, metadata management, data lineage, reconciliation, and enterprise data architecture.