Title – Sr Data engineer Role (Banking/Finance domain)
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:
13+ years of experience
· 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.
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