VP, Data Engineer

Role Description

The role involves leading the design, development, and optimization of scalable, cloud-native data platforms. Key responsibilities include owning ETL/ELT workflows, integrating and standardizing data, automating ingestion and transformation processes, enforcing data retention policies, and participating in Agile/Scrum ceremonies.

Key Responsibilities

• Own the architecture, design, and implementation of end-to-end ETL/ELT workflows using Azure Data Factory (ADF) and Azure Databricks for regulatory and compliance-driven data ingestion and transformation.
• Integrate, standardize, and normalize structured and unstructured data from multiple internal and external sources while enforcing strict data quality and governance controls.
• Build secure, auditable, and high-performance data pipelines supporting large-scale, sensitive financial datasets.
• Automate ingestion, transformation, and validation processes to enable near real-time analytics and regulatory reporting.
• Design and implement efficient storage formats, partitioning, and optimization strategies for fast data access and retrieval.
• Utilize Databricks and Delta Lake for distributed processing, ACID-compliant storage, versioning, and time-travel capabilities.
• Enforce data retention, archiving, and purging policies aligned with global regulatory and compliance requirements.
• Migrate legacy application logic into modern Azure Databricks, Data Lake, and SQL-based architectures.
• Maintain comprehensive data lineage, metadata management, and audit trails using Azure Purview or equivalent frameworks.
• Partner with data governance, risk, and compliance teams to define data standards, access controls, and security requirements.
• Implement and manage CI/CD pipelines using GitHub and GitHub Actions, enabling automated testing, version control, and reliable deployments.
• Review code, enforce engineering best practices, and support production deployments and operational stability.
• Provide technical leadership and mentorship to data engineers, setting standards and best practices across the organization.

Qualifications And Skills

• Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 10–15 years of hands-on experience in data engineering, preferably within financial services or other regulated industries.
• Required Technical Expertise:
• Azure Databricks (clusters, jobs, notebooks, Delta Lake, performance tuning)
• PySpark (RDDs, DataFrames, Spark SQL, optimization techniques)
• Azure Cloud Services: Azure Data Factory (ADF), ADLS Gen2, Azure Synapse, Azure Functions, Azure DevOps / GitHub
• Python for data engineering and automation workflows
• SQL (complex queries, performance optimization, large-scale datasets)
• Preferred / Nice-to-Have Skills:
• Experience designing and supporting enterprise-scale ETL/ELT pipelines
• Strong understanding of Delta Lake, medallion architecture (Bronze/Silver/Gold), and distributed data processing
• Familiarity with data governance, security, encryption, and RBAC in cloud-native environments
• Experience with CI/CD best practices and automated deployment pipelines
• Exposure to BI and visualization tools such as Power BI or Tableau
• Familiarity with Anaplan or other enterprise planning platforms is a plus, particularly in supporting downstream financial analytics or planning use cases
• Exposure to or hands-on experience with AI agents, intelligent automation, or GenAI-enabled data workflows is a strong plus
• Excellent analytical, communication, and cross-functional collaboration skills

About the role

Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries.

Benefits

SMBC Group provides a Hybrid workforce model that allows employees to work from home or an SMBC office. Employees must live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during the interview process. SMBC requires reasonable accommodations during the application process for applicants with disabilities consistent with applicable federal, state, and local law.