Lead Data Engineer Capital Markets

We are looking for Lead Data Engineer Capital Markets - Hybrid for our client in Jersey City, NJ.

Job Title: Lead Data Engineer Capital Markets

Job Location: Jersey City, NJ

Job Type: Contract

Job Overview:

Pay Range: $65/hr - $70/hr

Requirement/Must Have:

• Technical: Snowflake, Oracle PL/SQL, DBT, Python, any BI reporting tool.
• Strong hands-on experience with Snowflake, including data modeling, performance optimization, and cost management.
• Advanced proficiency in Python for data processing, automation, and integration.
• Solid experience in Oracle PL/SQL, including complex queries, procedures, and performance tuning.
• Experience with at least one enterprise reporting or BI tool.
• Proven leadership skills with experience leading teams and owning project delivery.
• Strong customer interaction and stakeholder management skills.
• Experience driving governance forums and executive-level status reviews.
• Exposure to Generative AI, including use cases, tools, or solution implementation, is highly desirable.

Responsibilities:

• Design, develop, and optimize data solutions using Snowflake, Python, and Oracle PL/SQL.
• Develop and maintain reports and dashboards using standard BI/reporting tools to support business decision-making.
• Lead end-to-end project deliverables, ensuring quality, timeliness, and alignment with customer requirements.
• Drive and manage weekly and monthly governance calls, including status reporting, risk management, and stakeholder communication.
• Ensure all project tasks and milestones are completed on time with high quality standards.
• Provide technical leadership and mentorship to the team, reviewing designs and code to ensure best practices.
• Engage directly with customers to understand business needs, translate them into technical solutions, and manage ongoing interactions.
• Collaborate with cross-functional teams to ensure smooth delivery and adoption of solutions.
• Apply Generative AI concepts and tools where relevant to enhance data engineering, analytics, automation, and productivity use cases.
• Continuously identify opportunities for process improvement, automation, and innovation.