Senior Analytics & Tableau Lead Engineer

JP Morgan Chase

Chicago (IL)

On-site

USD 170,000 - 230,000

Full time

4 days ago
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Benefits offered by this job

Health insurance
Performance bonus

Job summary

JP Morgan Chase in Chicago seeks a Lead Software Engineer to provide technical direction across a complex analytics portfolio, mentor teams, and advance data-driven, trusted analytics and scalable engineering practices.

You will lead the design and delivery of Tableau-based dashboards, integrate data across warehouses, APIs, and cloud-enabled workflows while promoting responsible AI usage and robust validation standards.

Qualifications

  • Expert hands-on Tableau experience including complex dashboard design, development, troubleshooting, performance tuning, and production support.
  • Knowledge of analytical and BI tools, including Tableau and Qlik Sense and Grafana.
  • Project experience using SQL, Qlik Sense, Tableau, Python, R, and Alteryx or comparable tools.
  • Strong knowledge of data warehouses, data modeling, and connections to diverse databases, data types, and data structures.
  • Extensive API experience including designing, consuming, and troubleshooting REST APIs and BI platform integrations.
  • Python experience in analytics, data processing, automation, or BI development; experience with GitHub Copilot and AI-assisted development integration techniques.
  • Ability to lead a complex analytics portfolio and backlog, manage competing priorities, and deliver high-priority initiatives with measurable outcomes.
  • Experience mentoring developers and partnering with senior leaders, business stakeholders, technology teams, application owners, and data management teams.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations

Responsibilities

  • Lead design, development, optimization, and maintenance of complex, highly visible Tableau dashboards; guide architecture, performance, usability, and quality.
  • Deliver and oversee embedded Tableau dashboards and both packaged (.twbx) and un-packaged (.twb) workbooks.
  • Explore datasets for trends, outliers, and relationships; build interactive visualizations for stakeholder insights.
  • Mentor developers through technical guidance, design and code reviews, standards, and problem-solving.
  • Partner with technology teams, application owners, and data management on continuous-improvement roadmap including advanced analytics and cloud adoption.
  • Lead data integration across warehouses, SQL and NoSQL databases, and APIs; use Python and automation to improve reliability.
  • Promote effective GitHub Copilot use and AI-assisted development integration within team workflows.
  • Drive adoption of enterprise-authorized AI-assisted engineering practices to improve quality, delivery speed, and operational outcomes with robust validation standards.
  • Define, monitor, and report key management metrics for a global operations program health and performance.
  • Partner with senior leaders to advance analytics and improve operational efficiency, cost modeling, capacity planning, quality.
  • Define, design, and manage high-priority strategic initiatives with governance, milestones, and delivery plans.

Skills

Tableau
Tableau dashboards
Qlik Sense
Grafana
Python
R
Alteryx
APIs

Tools

SQL
Tableau
Qlik Sense
Python
R
Alteryx

Job description

JP Morgan Chase in Chicago seeks a Lead Software Engineer to provide technical direction across a complex analytics portfolio, mentor teams, and advance data-driven, trusted analytics and scalable engineering practices.

You will lead the design and delivery of Tableau-based dashboards, integrate data across warehouses, APIs, and cloud-enabled workflows while promoting responsible AI usage and robust validation standards.

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