Lead Data Engineer- Analytics-BI

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Job Summary
As a Lead Data Engineer at JPMorgan Chase within the Wholesale Credit Risk team, you will lead the strategic transformation of our data landscape.

This role offers you the opportunity to modernize our data infrastructure, enabling advanced analytics and data-promoten decision-making across the organization.

You will inspire and guide a team of data engineers to optimize data sourcing strategies and deliver innovative, scalable, and secure data solutions.

Join us to promote impactful change and foster a culture of collaboration, integrity, and continuous improvement.

Key Responsibilities:


* Lead the design and implementation of modern, scalable analytics solutions across hybrid cloud and on-prem environments, supporting both operational and strategic business needs.


* Develop and maintain high-quality analytical models, dashboards, and reporting frameworks to enable data-driven decision-making.


* Drive initiatives to consolidate, standardize, and modernize analytics platforms and reporting tools to ensure consistency and accuracy of business insights.


* Apply and promote best practices in data analysis, data visualization, security, risk management, regulatory compliance, and automation.


* Collaborate cross-functionally with data engineering, software, and business teams to deliver analytics solutions aligned with business objectives.


* Ensure data quality, governance, and metadata management across all analytics assets and outputs.


* Troubleshoot and resolve complex issues related to data quality, interpretation, and business logic.


* Present analytical strategies, key insights, and project updates to senior stakeholders and executive leadership.


* Mentor and develop a team of data analysts and data scientists, fostering a culture of continuous learning and innovation.

Required Skills & Experience:


* 7+ years in data analytics, business intelligence, or data science, with a proven track record of leading large-scale analytics and transformation projects in hybrid cloud and on-prem environments.


* Deep expertise in statistical modeling, data analysis, business intelligence tools (e.g., Tableau, Power BI, Qlik), and cloud analytics platforms (AWS, Azure, GCP).


* Strong experience architecting and optimizing analytical data systems and reporting frameworks.


* Mastery of data visualization, data quality frameworks, data governance, and metadata management.


* Proficiency in enterprise-grade analytics languages (e.g., Python, R, SQL) and analytics tools.


* Solid background in data security, risk management, and regulatory compliance.

Attitude & Behavioral Traits:


* Action-oriented, decisive, drives results systematically.


* Skilled at assessing risk and making decisions with a holistic, big-picture perspective.


* Demonstrates a...