Data Engineer - Capital Markets

Sumitomo Mitsui Banking Corporation•New York, NY

1d•$97,000 - $156,000•Hybrid

About The Position

SMBC Group is a top-tier global financial group with a 400-year history, offering diverse financial services. Headquartered in Tokyo, it has over 130 offices and 80,000 employees worldwide. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company and one of Japan's largest banking groups. In the Americas, SMBC Group operates in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru, providing commercial and investment banking services. 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. We are seeking a Senior Databricks Engineer with deep AWS expertise to build, optimize, and maintain our enterprise data Lakehouse infrastructure. In this role, you will be responsible for designing high-performance data pipelines, implementing regulatory and real time reporting along with advanced analytics environments, and ensuring seamless integration between Databricks and core AWS services to support real-time financial trading data consumption.

Requirements

4+ years of hands-on experience in architectural design and development within the Databricks platform, alongside 3+ years working in an AWS cloud environment.
Proven proficiency in automated deployments using Databricks Asset Bundles (DABs), Terraform (specifically the Databricks and AWS providers), and standard Git pipelines (e.g., GitHub Actions, GitLab CI/CD, or AWS CodePipeline).
Advanced programming skills in Python (PySpark) and SQL for complex data manipulation and transformation.
Strong understanding of Apache Spark internals, Delta Lake mechanics, and streaming data concepts (e.g., interacting with Amazon MSK or Kafka data streams).
Proven experience building production-grade ETL/ELT pipelines, handling data schema validation, and cleansing raw capture feeds.

Nice To Haves

Databricks Certified Data Engineer Professional or AWS Certified Data Engineer – Professional is highly advantageous.

Responsibilities

Design and implement robust data pipelines using the Databricks Medallion Architecture (Bronze, Silver, Gold layers) to process structured and unstructured data.
Develop, scale, and orchestrate complex data workflows utilizing Databricks Jobs and Delta Live Tables (DLT).
Standardize and automate the deployment of Databricks assets, workspace configurations, and code pipelines across Dev, QA, and Production environments.
Ensure seamless data cataloging, storage, and movement across the AWS ecosystem, specifically integrating Databricks with Amazon S3, AWS Glue, and AWS IAM for secure access control.
Tune Spark clusters, optimize Delta Lake storage (e.g., Z-Ordering, partitioning), and manage compute costs within the AWS environment.
Implement fine-grained data access controls, data lineage, and auditing using Unity Catalog or native cloud security controls.
Partner with Data Scientists, Risk Managers, and downstream analytics teams to deliver clean, business-ready data views for reporting and AI modeling.