Search by job, company or skills

Vice President/Director, Data Framework Engineering

SMBC Group
12-14 Years
Singapore
  • Posted 5 hours ago
  • Be among the first 10 applicants

Job Description

Key Responsibilities

  • Define and own the strategic roadmap for enterprise data engineering frameworks supporting the bank-wide Data Lakehouse platform.
  • Lead the design, development, and lifecycle management of reusable frameworks for data ingestion, transformation, serving, orchestration, data quality, reconciliation, lineage, and observability.
  • Establish enterprise standards for metadata-driven and manifest-based development, enabling configuration-over-code implementation patterns and accelerated source onboarding.
  • Develop standardized ingestion capabilities supporting batch, streaming, CDC, API, event-driven, file-based, and real-time integration patterns.
  • Build reusable transformation frameworks supporting Bronze, Silver, and Gold data processing layers with configurable business rules and enrichment logic.
  • Define bank-wide framework standards for SCD Type 1, Type 2, Type 3, reference data management, hierarchy processing, and master data integration.
  • Establish enterprise data quality frameworks providing profiling, validation, completeness, accuracy, timeliness, consistency, and integrity controls.
  • Build reconciliations and control frameworks supporting source-to-target balancing, financial controls, regulatory controls, exception management, and operational attestation.
  • Develop scalable data serving frameworks supporting data products, APIs, Delta Sharing, self-service analytics, AI consumption, and Power BI reporting.
  • Lead engineering of framework capabilities for metadata management, lineage, auditability, traceability, security, and policy enforcement.
  • Drive adoption of Databricks Lakehouse capabilities including Delta Lake, Spark, Unity Catalog, Workflows, Auto Loader, and enterprise-scale pipeline standards.
  • Partner with Data Design & Models teams to operationalize canonical models, semantic layers, manifest standards, and reusable engineering patterns.
  • Improve engineering productivity through framework automation, reusable assets, CI/CD pipelines, Infrastructure-as-Code, automated testing, and AI-assisted development.
  • Define and monitor framework KPIs covering onboarding speed, code reuse, deployment frequency, platform reliability, data quality, and developer productivity.
  • Build and lead high-performing regional and offshore engineering teams while providing technology leadership across Data Engineering, Analytics, AI, Risk, Finance, and Regulatory initiatives.

Requirements & Experience

  • Bachelor's or Master's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or related discipline.
  • 12+ years of experience in enterprise data engineering, data platform engineering, or large-scale data transformation programs.
  • Proven experience designing and building enterprise-scale data engineering frameworks rather than project-specific pipelines.
  • Extensive experience developing reusable frameworks that improve delivery speed, developer productivity, platform consistency, and operational resilience.
  • Demonstrated success implementing metadata-driven and manifest-driven engineering architectures at enterprise scale.
  • Deep expertise in modern Data Lakehouse platforms, including Databricks, Delta Lake, Spark, Unity Catalog, and cloud-native data services.
  • Strong hands-on experience building ingestion, transformation, serving, data quality, reconciliation, orchestration, and monitoring frameworks.
  • Experience designing highly scalable platforms capable of onboarding hundreds of source systems and supporting thousands of data pipelines.
  • Strong knowledge of distributed processing, Spark optimization, workload management, performance tuning, and large-scale data operations.
  • Experience implementing CI/CD, DevSecOps, Infrastructure-as-Code, automated testing, observability, and platform engineering best practices.
  • Hands-on experience with Python, SQL, Spark, PySpark, Git, and modern engineering toolchains.
  • Strong knowledge of enterprise metadata management, lineage, governance, cataloging, and platforms such as Collibra and Unity Catalog.
  • Experience enabling self-service analytics, semantic layers, Power BI integration, and data product architectures.
  • Banking and financial services experience across Risk, Finance, Treasury, Regulatory Reporting, Customer, Compliance, Fraud, and Corporate Banking data domains is highly preferred.
  • Proven track record delivering enterprise framework platforms that significantly reduce development effort, accelerate onboarding time, improve engineering productivity, and support large-scale regulatory and business data programs.

More Info

Job Type:
Permanent Job
Industry:
Other
Function:
Data Engineering
Employment Type:
Full time

About Company

Job ID: 152372605

Last Updated: 15-08-2026 07:23:46 PM
Homejobs in SingaporeVice President/Director, Data Framework Engineering

Similar Jobs

Vice President/Director, Data Framework Engineering

sumitomo mitsui banking corporation singapore branch
S
Singapore

Skills:

Data Transformation, Metadata Management, Power Bi, Pyspark, Automated Testing, Sql, Git, Data Quality, DevSecOps, Spark, Databricks, Python, monitoring frameworks, CI CD, self-service analytics, Unity Catalog, Data Lakehouse, Delta Lake, data ingestion, Infrastructure-as-Code

Director/Vice President, Technology, Cloud Platform

Temasek
Singapore

Skills:

Docker, AWS, Kubernetes, Azure, Gcp, SaaS services, Containerisation technologies, CI CD pipelines, cloud platforms

Beware of Scammers

We don’t charge money for job offers

Know More