> Markdown version of [/jobs/ext/2599015-finance-data-insights-pxt-analytics](https://www.wearedevelopers.com/jobs/ext/2599015-finance-data-insights-pxt-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Finance Data & Insights (PXT) - Analytics... - **Company:** JPMorgan Chase & Co. - **Location:** Columbus, OH, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Microsoft Word, Microsoft Excel, Agile Methodology, Artificial Intelligence, Data Analysis, Confluence, JIRA, Information Systems, Data Validation, Information Engineering, Microsoft Office, Microsoft Visio, Pivot Tables, Microsoft PowerPoint, Scrum Methodology, Microsoft SharePoint, SQL Databases, Tableau (Software), Unstructured Data, GitHub Copilot, Performance Monitor, Software Coding, Alteryx, Databricks - **Published:** August 4, 2026 - **Apply:** https://www.juju.com/job/00000000gm7h58 ## About the Role + Bachelor's degree in Business Analytics, Data Science, Information Systems, Statistics, or a closely related field; 3+ years of relevant experience in analytics, business intelligence, or a data-focused role + Experience in or a keen desire to learn Agentic Frameworks and AI tools(GitHub Copilot, Claude etc.) + Experience building dashboards and performance reporting. + Demonstrated proficiency with Databricks, BI Tools (ThoughtSpot, Alteryx, Tableau etc.), Jira, Visio, SharePoint, Confluence and Microsoft Office (Word, Excel, PowerPoint, Pivot Tables). + Must possess good understanding of SQL and should be able to write complex SQL queries for data analysis. + Agile Experience with tools such as Jira and understanding of Backlog Prioritization Techniques. Preferred qualifications, capabilities, and skills: + Background/Experience in product development or related experience, preferred. + Hands-on experience writing code and automating processes to source, transform and analyze data from multiple sources including structured and unstructured data preferred ## Description + Lead and support features by collecting user requirements and feedback from business partners and project leads in formal and informal settings and use agentic tools across all work processes to deliver work efficiently + Own Epics and Stories to deliver features fulfilling the feature goals, including writing, and refining Epics and Stories in JIRA with Scrum team, and partnering with Agile lead on sequencing. + Maintain and prioritize the product backlog along with other analysts and product leads and identify potential project roadblocks, bottlenecks, and dependencies by understanding how the multiple project teams interact with one another. + Partner with Data Engineering/BI teams to help deliver curated datasets and dashboards aligned to defined requirements. + Execute data validation and UAT (run test cases, reconcile results, log defects, track fixes) and communicate status to stakeholders. + Maintain clear documentation (data definitions, report logic notes, release notes, simple user guides) to support adoption and reduce repeat questions. + Follow established processes for access requests, controls, and data quality procedures; escalate risks, blockers, or unclear requirements promptly. ## Related Videos - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Integrate your Cognitive Assistant with 3rd-party DBs and software](https://www.wearedevelopers.com/videos/249-integrate-your-cognitive-assistant-with-3rd-party-dbs-and-software) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)