Hadoop/Spark Software Engineer

We are seeking an experienced Hadoop Engineer with a strong background in data migration, ETL, and Hadoop ecosystems to support mission-critical data initiatives in the banking sector. The ideal candidate will have hands-on expertise working in Hive and Spark environments, migrating data from MS SQL Server to Hadoop/Hive, and building scalable, performant data models.

This role requires prior experience in the banking or financial services industry and a deep understanding of data governance, compliance, and security protocols within that context.

Eligibility:USC/EAD

Key Responsibilities:

• Operate effectively in Hadoop/Hive environments, leveraging Apache Spark

• Perform data migration from MS SQL Server to Hadoop/Hive platforms

• Develop and optimize SQL-based ETL pipelines

• Work with data modeling and large-scale structured/unstructured datasets

• Collaborate with DevOps using Jenkins, GitHub, and Confluence

• Partner with cross-functional teams to support data warehousing and analytics projects

• Follow best practices in data security, privacy, and compliance standards relevant to banking

Must-Have Skills:

• BANKING INDUSTRY EXPERIENCE (Required)

• Strong experience in Hadoop, Hive, and Spark environments

• Proven hands-on work migrating data from MS SQL Server to Hadoop/Hive

• Proficient in SQL Server, ETL, and data modeling

• Familiarity with Big Data ecosystems and architecture

• Experience with Confluence, Jenkins, and GitHub

Preferred Qualifications:

• Experience with performance tuning in Spark/Hive

• Familiarity with data quality frameworks and automation

• Knowledge of compliance standards (e.g., SOC2, PCI DSS) in financial environments

• Strong problem-solving skills and ability to work independently