Data Science Engineer - W2 Job Rutherford area,New Jersey USA,IT/Tech

Position: Data Science Engineer - W2 ONLY

We are seeking a highly motivated Data Engineer to join our Retail & Wealth technology team. The ideal candidate will possess strong expertise in SQL, data engineering, quality engineering fundamentals, and scripting, with experience supporting large-scale data platforms and AI-driven initiatives. This role will focus on building, enhancing, and maintaining data pipelines, ensuring data quality, and enabling analytics and AI use cases across business functions.

Key Responsibilities

Design, develop, optimize, and maintain scalable data pipelines and data integration solutions.
Develop and support data models, ETL/ELT processes, and database solutions using SQL and scripting languages.
Perform data profiling, validation, reconciliation, and quality assurance activities to ensure data integrity and accuracy.
Collaborate with business analysts, data scientists, product teams, and technology partners to deliver data-driven solutions.
Support AI and advanced analytics initiatives by preparing and transforming large datasets for model development and reporting.
Implement and maintain automated testing frameworks and quality engineering practices for data applications.
Troubleshoot data issues, performance bottlenecks, and production incidents while ensuring timely resolution.
Participate in code reviews and promote development best practices, standards, and governance.
Develop monitoring and alerting solutions to proactively identify and resolve data quality issues.
Contribute to continuous improvement initiatives focused on automation, efficiency, and scalability.

Required Qualifications

6–10 years of experience in Data Engineering, Data Warehousing, or related technology roles.
Strong hands‑on experience with SQL and complex query optimization.
Experience with scripting languages such as Python, Shell Scripting, or similar technologies.
Solid understanding of data engineering concepts, ETL/ELT development, and data integration frameworks.
Strong knowledge of Quality Engineering (QE) fundamentals, testing methodologies, and automation practices.
Experience working with relational and distributed database technologies.
Understanding of data quality, data governance, and metadata management principles.
Strong analytical, problem‑solving, and debugging skills.
Excellent communication and stakeholder management abilities.
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.

Preferred Qualifications

Experience supporting AI, Machine Learning, or advanced analytics initiatives.
Exposure to cloud platforms such as AWS, Azure, or GCP.
Experience with big data technologies and modern data platforms.
Knowledge of CI/CD pipelines and Dev Ops practices.
Experience with in Retail Banking, Wealth Management, Financial Services, or related domains.
Familiarity with Agile/Scrum development methodologies.

Technical Skills Required

SQL
Python or Shell Scripting
ETL/ELT Development
Data Quality & Validation
Quality Engineering Fundamentals
Database Design & Optimization
Data Modeling

Preferred

AI/ML Data Preparation
Spark, Hadoop, or Distributed Data Platforms
CI/CD Tools
Strong ownership and accountability
Critical thinking and problem-solving
Collaboration and teamwork
Ability to work in a fast‑paced environment

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