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# Manager - Data Engineering

- **Company:** American Express Company
- **Location:** New York, NY, United States
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Big Data, Cloud Database, Data Auditing, Data Validation, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Executive Information Systems, JSON, Python (Programming Language), Machine Learning, Microsoft PowerPoint, Power BI, SQL Databases, Data Classification, Large Language Models, Powerquery, Microsoft Fabric, Information Technology, Data Analytics, Data Management, Restful APIs, Data Pipelines, Powerapps
- **Published:** October 10, 2026
- **Apply:** https://www.dice.com/job-detail/a936d926-a78f-4e4b-a3da-ad40c79ce3f1

## About the Role

Seeking an experienced, data-driven professional to support the Platform Health Program by analyzing complex technology investment and portfolio datasets, developing scalable data and reporting solutions, and delivering actionable insights that improve portfolio transparency, operational efficiency, and strategic decision-making.

The ideal candidate is based in New York and brings a combination of data analytics, engineering, business intelligence, and technology portfolio management experience, with the ability to collaborate closely with Technology, Product, Finance, and Portfolio Management teams., * Strong experience in data analytics, data engineering, or technology portfolio analytics, with hands-on proficiency in Python, SQL, JSON, data modeling, ETL/ELT, REST APIs, and large-scale data analysis.

 * Proficiency in Power BI, Microsoft Fabric, DAX, Power Query, Excel, and PowerPoint, with experience developing executive dashboards, automated reports, and portfolio performance visualizations.
 * Experience working with technology investment, financial, or portfolio management datasets, including platforms such as IBM Apptio or equivalent solutions.
 * Understanding of technology portfolio management, investment planning, budget tracking, financial forecasting, resource capacity, and project delivery performance.
 * Experience applying AI/ML, LLM-enabled analytics, predictive modeling, and workflow automation to improve data insights, reporting accuracy, and operational efficiency.
 * Knowledge of data integration, database management, data quality validation, reporting automation, and data governance best practices.
 * Familiarity with Microsoft Power Platform, including Power Apps and Power Automate, as well as cloud-based data and analytics environments.
 * Strong analytical, problem-solving, communication, and stakeholder management skills, with the ability to translate complex data into clear, actionable recommendations for leadership.
 * Bachelor's degree in Computer Science, Engineering, Data Analytics, Business Analytics, or equivalent professional experience; advanced degree preferred.

## Description

* Portfolio Performance & Analytics: Monitor and analyze technology portfolio performance across investments, budgets, resource allocation, forecasts, delivery schedules, and operational health to identify trends, risks, variances, and opportunities for improvement.
 * Data Analysis & Integration: Gather, consolidate, and analyze large, disparate technology and financial datasets, leveraging Python, SQL, APIs, and data pipelines to improve data accessibility, accuracy, and reporting efficiency.
 * Business Intelligence & Executive Reporting: Develop dashboards, Power BI reports, PowerPoint presentations, and on-demand analytics to communicate portfolio performance, investment insights, and key findings to leadership and stakeholders.
 * Investment & Resource Optimization: Partner with Portfolio Management, Finance, and Technology teams to evaluate investment priorities, resource capacity, budget utilization, and delivery risks, providing data-driven recommendations to support portfolio planning and decision-making.
 * AI & Process Automation: Leverage AI-assisted analytics, machine learning, and automation capabilities to enhance data classification, forecasting, reporting accuracy, and portfolio management processes.
 * Data Quality & Governance: Support data validation, reconciliation, lineage, and reporting standards to ensure consistent, reliable, and transparent portfolio information across multiple data sources.
 * Cross-Functional Collaboration: Work closely with Technology, Product, Finance, and business stakeholders to understand reporting needs, validate findings, align portfolio metrics, and translate business requirements into actionable insights and technical solutions.
 * Continuous Improvement & Innovation: Proactively identify opportunities to streamline reporting, enhance Platform Health transparency, improve portfolio governance, and develop scalable data solutions that support strategic technology investment decisions.