Data Engineer

About the role

Contract role with a strong possibility of extension and/or conversion, based in Rutherford, NJ. This position requires a hybrid schedule of 2-3 days onsite per week. Join one of the world's most renowned global banks and trusted brands with over 200 years of continuously evolving financial services worldwide. You will work alongside some of the smartest minds in the industry who are excited to share their knowledge and learn from you.

Contract Duration: 6+ Months

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 5–8 years of experience in data engineering, SQL development, data analysis, or a related field.
• Strong proficiency in SQL and experience with relational databases and data warehousing concepts.
• Experience with ETL tools, data pipeline frameworks, and big data technologies.
• Knowledge of Quality Engineering (QE) fundamentals, including data validation, testing frameworks, and automation.
• Strong problem-solving, analytical, and troubleshooting skills.
• Excellent communication and stakeholder management abilities.
• Experience working in complex, cross-functional environments.

Desired Skills

• Strong preference for candidates with Risk and Wealth experience.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes to support analytics and operational use cases.
• Develop and optimize complex SQL queries for data extraction, transformation, and validation.
• Implement data quality checks, validation rules, and QE practices to ensure accuracy, consistency, and reliability of data.
• Partner with business and technology teams to translate requirements into technical data solutions.
• Analyze and troubleshoot data issues, performing root cause analysis and implementing fixes.
• Drive data governance and standardization efforts across systems and platforms.
• Support system integration and data flow across multiple applications and environments.
• Lead data-related aspects of system changes, from requirements through development, testing (QE), and deployment.
• Collaborate with QE teams to define test strategies, automate data validation, and ensure end-to-end system quality.
• Communicate risks, dependencies, and impacts of data solutions to stakeholders.
• Ensure compliance with data governance policies, regulatory requirements, and best practices.

Schedule

Hybrid schedule requiring 2-3 days onsite per week.