VP, Data Engineer - DataBricks

SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, 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. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges. In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd. SUMMARY Join SMBC’s Compliance Technology team as a Data Engineer specializing in Azure and Databricks. You will architect and build secure, scalable data pipelines and a cloud‑native data platform that powers real‑time compliance analytics and regulatory reporting across global markets. Work collaboratively as a team player on mission‑critical projects involving complex financial datasets, leveraging Azure Data Factory, Databricks, Delta Lake, and Python to transform raw data into trusted, governed insights. This is a high‑impact role where a motivated self‑starter owns, end‑to‑end data engineering initiatives, collaborates with governance teams, and influence the architecture of SMBC’s next‑generation compliance systems. PRINCIPAL DUTIES & RESPONSIBILITIES Own the design and implementation of ETL workflows using Azure Data Factory and Databricks for compliance‑related data ingestion and transformation. Integrate and normalize data from multiple structured and unstructured sources, ensuring adherence to strict data quality governance framework. Develop secure, auditable, and optimized pipelines for performance and reliability across sensitive financial datasets. Automate ingestion and transformation processes to enable real‑time compliance analytics and reporting. Implement efficient storage formats and partitioning strategies for fast loading and retrieval. Utilize Databricks and Delta Lake for distributed processing and versioned data storage. Enforce data retention, archiving, and purging policies aligned with global regulatory requirements. Migrate legacy application logic into modern Azure Databricks/Data Lake and SQL environments. Maintain comprehensive data lineage, metadata, and audit trails using Azure Purview or custom frameworks. Collaborate with governance teams and compliance analysts to define requirements and manage access controls. Participate in Agile development cycles, sprint planning, and compliance reviews. Review code changes and support production deployments. JOB SPECIFICATIONS 5+ years of experience in data engineering within financial services, preferably compliance/regulatory. Advanced proficiency in SQL, Python, and Azure Databricks. Hands‑on experience with Azure Data Factory, Databricks notebooks, and ADLS. Expertise in data wrangling, modeling, and analytics enablement for compliance use cases. Experience integrating Microsoft ADF and Databricks for complex ETL development. Familiarity with data governance, quality frameworks, and audit processes. Strong communication and collaboration skills. Experience with Git/GitLab and CI/CD tools such as Azure DevOps. Preferred: Certifications in Azure Data Engineering, Databricks, or Financial Compliance Technology. Preferred: Bachelor’s or Master’s in Computer Science, Data Engineering, or related field SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA‑registered roles for which in‑office attendance for the entire workweek is required. SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at View email address on click.appcast.io. EOE, including Disability/veterans #J-18808-Ljbffr SMBC