Data Science Engineer - W2 ONLY

Job Overview 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 DevOps practices. • Experience within Retail Banking, Wealth Management, Financial Services, or related domains. • Familiarity with Agile/Scrum development methodologies. Technical Skills Required • SQL • Python or Shell Scripting • Data Engineering • ETL/ELT Development • Data Quality & Validation • Quality Engineering Fundamentals • Database Design & Optimization • Data Modeling Preferred • AI/ML Data Preparation • Cloud Technologies (AWS/Azure/GCP) • Spark, Hadoop, or Distributed Data Platforms • CI/CD Tools • Git Version Control Competencies • Strong ownership and accountability • Critical thinking and problem-solving • Attention to detail • Collaboration and teamwork • Ability to work in a fast-paced environment • Continuous learning mindset