Senior Data Engineer

 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.

The anticipated salary range for this role is between $115,000.00 and $205,000.00. The specific salary offered to an applicant will be based on their individual qualifications, experiences, and an analysis of the current compensation paid in their geography and the market for similar roles at the time of hire. The role may also be eligible for an annual discretionary incentive award. In addition to cash compensation, SMBC offers a competitive portfolio of benefits to its employees.

Role Description

We are currently seeking a talented and motivated senior Azure Data Engineer to join our Risk Technology Team. The role will be responsible for developing, deploying solutions for risk, regulatory, compliance projects on Azure platform and be at the forefront of on-prem to cloud migration initiative.

The Azure Cloud Engineer strategizes, designs, develops and work with a team of dynamic and passionate data engineers to deliver automated cloud infrastructure and DevOps solutions. The incumbent will play a key role in supporting the growth and scale of our Azure cloud-based technology infrastructure. This role is also responsible for complex interface process development, troubleshooting issues, supporting weekend maintenance and production support.

Role Objectives

• As an Azure Databricks Architect, responsible for the administration, configuration, and optimization of the Azure Databricks platform.
• Provide technical expertise to deploy applications on the platform, and work with data engineers, data scientists, and other stakeholders to ensure the platform meets their requirements.
• Manage the infrastructure and collaborates with teams to ensure it integrates with all components, including network, security, and remote access.
• Databricks Cluster configuration, Unity catalog repository configuration.
• Seamless integration with On-prem databases and Power BI reports
• Build large-scale batch and real-time data pipelines with data processing frameworks in Azure cloud platform.
• Partner with architects, engineers, information analysts, business, and technology stakeholders for developing and deploying enterprise grade platforms that enable data-driven solutions.
• Provide technical guidance on technology implementation and architectural changes.
• Coordinating with platform, APIM, Azure DevOps, and Support.
• Analyze and design technical solutions on Azure to address business needs.
• Develop, test, and modify software to improve efficiency of data platforms and applications.
• Proficient in Python coding and frameworks knowledge.
• Ability to migrate the Data Science models written on native python language to the multi node Databricks compute.
• Ability to own projects from end to end, working with business stakeholders, IT teams, data stewards, and 3rd party companies to ensure accurate and insightful outcomes.
• Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards.
• Enable streaming data use-cases and standard design patterns in a big data