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United Airlines

Flies passengers and cargo worldwide from US hubs

Senior Analyst - Finance Data Capability

Data Management +1Updated on Nov 13
Full-timeGurugram, Haryana, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Finance, Accounting, Information Systems, Computer Science, or a related field.
  • At least 4 years of finance and/or technology experience.
  • Experience in finance analytics, data analytics, finance systems, or technology transformation.
  • Strong expertise in finance data, reporting, analytics, data modeling, and master data governance.
  • Experience working with large, complex datasets using platforms such as Databricks, Snowflake, Foundry, or SQL Server.
  • Hands-on experience with Power BI and/or Tableau for reporting and visualization.
  • Working knowledge of Oracle EDM; Oracle ERP and Oracle EPM knowledge is complementary.
  • Strong proficiency in SQL and data analysis.
  • Experience using Python for analytics, automation, or process improvement.
  • Experience with Alteryx or similar ETL/data transformation tools.
  • Familiarity with generative AI tools such as Copilot and ChatGPT, AI-assisted analytics, and agentic workflows or intelligent automation.
  • Strong analytical and problem-solving skills and the ability to translate complex data into actionable business insights.
  • Ability to independently identify and implement opportunities to improve finance processes through data, automation, AI, and scalable technology solutions.
  • Excellent verbal and written communication skills and the ability to present complex data, AI-driven insights, and process improvements to finance and non-finance stakeholders.
  • Strong understanding of how people, processes, data, and technology, including AI and automation, combine to build scalable and sustainable capabilities.
  • Ability to work independently and proactively identify opportunities to embed AI, automation, and improved data structures into existing workflows.

Responsibilities

  • Support cross-functional collaboration to assess and redesign finance data processes and technical landscapes, focusing on simplification, standardization, and end-to-end optimization aligned with enterprise goals.
  • Work with large and complex datasets across finance domains, ensuring scalable handling, efficient processing, and performance optimization across systems and data platforms.
  • Evaluate and embed generative AI and agentic solutions, such as copilots, autonomous workflows, and intelligent pipelines, to reimagine finance processes, reduce manual effort, and accelerate decision-making cycles.
  • Drive adoption of modern data and automation tools, including data platforms, Oracle, Alteryx, and Power BI, augmenting them with AI-driven insights, predictive analytics, and intelligent automation.
  • Develop and maintain financial data products, standardized KPIs, reusable datasets, and robust, dynamic data structures such as scalable data models and semantic layers to support evolving business needs and AI consumption.
  • Maintain and validate finance data mappings, transformation logic, and integrations, while exploring AI-assisted reconciliation, mapping automation, and anomaly detection.
  • Support finance data governance by defining data quality rules and partnering on controls and lineage, leveraging AI for continuous monitoring, exception handling, and automated remediation insights.
  • Collaborate cross-functionally to support finance data transformation initiatives, incorporating AI-first design principles, scalable data structures, and automation opportunities into solution architecture.
  • Partner with stakeholders, including Digital Technology and Finance, to align with enterprise strategy and identify and prioritize generative AI, agentic workflow, and big data use cases.
  • Support delivery of transformation initiatives, including milestones, timelines, and reporting, while piloting and scaling agent-based workflows and AI-enabled process automation.
  • Contribute to business cases by quantifying the impact of AI, automation, and improved data architecture, including scalability, speed, accuracy, and cost efficiency.

Desired Qualifications

  • A master's degree.
  • A Master of Business Administration.
  • Experience in the airline industry or a similar industry.
  • Experience with PMO/project management tools such as Smartsheet, JIRA, or similar platforms.
  • Understanding of finance data standards, governance, controls, and business processes across domains such as general ledger, accounts payable, accounts receivable, financial planning and analysis, and Treasury.
  • Experience establishing or driving data definitions, business rules, and reporting standards across functions.
  • Exposure to cloud-based data and analytics architectures such as AWS Data Lake, Azure, or similar platforms.

About the Company

United Airlines

Flies passengers and cargo worldwide from US hubs

United Airlines flies passengers and cargo across the United States and to destinations around the world, running a hub network that spans Chicago, Denver, Houston, Los Angeles, Newark, San Francisco, Washington Dulles and Guam. It was a founding member of Star Alliance, the global airline partnership that links its routes and frequent-flyer benefits with carriers such as Lufthansa and Air Canada. Travelers book seats in economy, premium and Polaris business cabins, and United earns money from fares, bag and seat fees, cargo, and its MileagePlus loyalty program, which sells miles to card partners. United traces its roots to Varney Air Lines, which began flying airmail in 1926, and is based in Chicago.

Company size
10,001+
Company stage
IPO
Headquarters
Chicago, IL
Founded
1926

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