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MA
Mizuho Americas Services LLC
Data Engineer
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$116,216 / year median in New Jersey
+11% projected growth
Job Description
Join Mizuho as a Data Engineer! The IT Data team is responsible for design and development of Data products for the entire firm. The team is embarking on an ambitious new project/implementation. "DEAL". It is the abbreviation for "Data Exchange and Abstraction Layer". It's the next generation, Data Mesh based platform implemented in the Mizuho Azure Cloud on Databricks. Data Mesh is a decentralized data architecture where data is owned and managed by the domain-specific teams that produce the data i.e. Banking, Finance etc., and curate it for downstream consumption. It emphasizes domain-oriented ownership, treating data as a product, providing a self-serve data platform, and using limited federated computational governance from the Data Architecture and Data Management Office. In this role you will be responsible for development of data solutions for the enterprise using innovative and cutting- edge technologies like AI tools / models. The solutions and software developed will be used for reporting and analytics by the entire firm globally. The data solutions developed will have to be accurate, timely and highly scalable. In this role you will be managing large data-sets with complex interdependencies. This is a hands-on software development role. You will be collaborating with teams firmwide to develop solutions. You'll support the development and maintenance of data pipelines on the Databricks Lakehouse platform using the medallion architecture (Bronze/Silver/Gold). You will work under the guidance of senior engineers to ingest, transform, and validate data, growing your skills across the modern data stack. Key Responsibilities Assist in building and maintaining ingestion pipelines that land raw data into the Bronze layer. Support Silver layer transformations under guidance: cleansing, deduplication, and schema enforcement. Write SQL and PySpark for defined transformation tasks. Run and monitor scheduled jobs; help investigate and resolve pipeline failures. Document pipeline logic, transformations, and fixes. Participate in code reviews as a reviewer-in-training and incorporate feedback on your own work. Learn team standards for version control, testing, and deployment. Required Qualifications 0-2 years of experience in data engineering, analytics, or a related technical role (internships and academic projects count). Foundational SQL skills (joins, aggregations, filtering). Python proficiency with basic OOPS knowledge . Understanding of core data concepts (tables, schemas, relational data). Willingness to learn Databricks, Spark, and cloud technologies. Familiarity with Git or a demonstrated ability to learn version control quickly.