Sr Data engineer Role

Sr Data Engineer Role Location – New York (Hybrid 3 to 5 days in the office) Client F2F interview is required Skills: ETL/Python/Data Modeling/Architecture/Snowflake (Financial experience) Responsibilities: Lead the design, development, and implementation of enterprise-scale data warehouse, reporting, and analytics solutions, preferably on cloud platforms such as Snowflake. Drive the adoption and integration of GenAI, LLMs, and modern AI/ML techniques for ETL automation, data enrichment, reporting commentary, and intelligent data distribution across the enterprise. Provide technical leadership and mentorship to a high-performing team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement. Collaborate with business stakeholders, technology partners, and cross-functional teams to define data strategy, requirements, and deliverables aligned with organizational goals. Champion modern SDLC practices, including automated testing, CI/CD, and agile methodologies, to ensure high-quality, scalable, and maintainable solutions. Drive automation, data quality, and best practices across all data engineering processes and solutions. Ensure robust data governance, security, and compliance throughout the data lifecycle. Manage stakeholder relationships, communicate project status, and proactively address risks and challenges. Champion the adoption of new technologies and methodologies to enhance data capabilities and business value. Required Technical Skills: 13+ years of experience in data engineering, data architecture, or related roles, with a proven track record of delivering enterprise-level solutions. Deep expertise in SQL, data modelling, ETL, and building scalable data pipelines. Strong hands-on experience with cloud data platforms (preferably Snowflake) and modern data engineering tools. Strong hands-on experience with Python, Shell scripting, and workflow automation. Demonstrated experience leveraging GenAI, LLMs, or AI/ML solutions for enterprise data, reporting, and analytics use cases. Proven ability to lead, motivate, and develop high-performing teams. Strong domain and functional knowledge in finance, investment banking, or related industries. Excellent problem-solving, analytical, and communication skills. Experience managing stakeholder relationships and delivering complex projects in a global environment. Strong understanding of modern SDLC, agile delivery, and innovation in data engineering. Additional Skills (Good to Have): Familiarity with Power BI, Apache Airflow, and OLAP tools. Exposure to regulatory and financial reporting requirements. Demonstrated track record of driving innovation and GenAI adoption in data engineering projects. Passion for continuous learning, business impact, and solution-oriented leadership. E-Solutions