Sr Manager Finance & Operations Data Enablement

LSG Sky Chefs•Irving, TX

22h•Hybrid

About The Position

Lead the development and execution of LSG’s Data, Analytics, and Modeling (DAM) capability to accelerate data-enabled decision-making across Operations and Finance. This role will bridge business priorities, modern data architecture, and practical execution by rapidly ingesting, modeling, and translating operational and financial data into scalable insights, tools, and use cases that improve performance, reduce dependency on manual processes, and support LSG’s broader data-enabled operating model.

Requirements

Bachelor’s degree in Finance, Accounting, Economics, Engineering, Data Analytics, or a related field (required)
6–10+ years of progressive experience across a combination of finance, operations, and data/analytics roles, ideally in operations-heavy, manufacturing, logistics, or similar environments
Proven track record of designing and building data-enabled operating models, translating operational and financial requirements into scalable data, analytics, and decision frameworks
Hands-on experience developing end-to-end data solutions across ingestion, modeling, and insight generation
Experience working with modern data platforms such as Databricks and/or Snowflake, and familiarity with data ingestion tools (e.g., Fivetran or similar)
Working knowledge of modern data architecture concepts, including acquisition (landing), domain (harmonization), and product layers
Strong understanding of operational and financial drivers, including cost structures, productivity metrics, and performance management
Experience with data visualization and reporting tools (e.g., Power BI or similar), with the ability to translate data into clear, actionable insights
Strong analytical, problem-solving, and communication skills, with the ability to engage both executive and operational stakeholders
Demonstrated ability to operate in ambiguous environments, building solutions from the ground up and driving cross-functional collaboration
Demonstrated ability to operate as a hybrid specialist across data, operations, and finance, rather than within a single functional discipline

Nice To Haves

Advanced degree or certification (e.g., MBA, MS, or equivalent) (preferred)

Responsibilities

Identify, prioritize, and deliver high-impact use cases across Operations and Finance (e.g., labor productivity, revenue capture, costing, and operational performance).
Develop end-to-end solutions that move from raw data to actionable insight, enabling faster and more effective decision-making.
Ensure outputs are embedded into daily and weekly operating rhythms, driving measurable business impact.
Design and implement practical data ingestion solutions for priority use cases using APIs, system extracts (e.g., SAP, CBASE, ARIS), and external tools.
Enable rapid access to data by working independently, while maintaining alignment with enterprise data standards.
Partner with IT to transition successful ingestion approaches into scalable, enterprise-supported pipelines over time.
Build and establish initial DAM capabilities, including business-ready data models that translate raw data into meaningful operational and financial insights.
Apply modern data architecture concepts, including acquisition (landing), domain (harmonization), and product layers, to structure and standardize data.
Develop reusable frameworks and logic (e.g., cost models, labor drivers, revenue tracking) that can scale across locations.
Translate complex data into clear, actionable insights that support operational and financial decision-making.
Develop intuitive reporting outputs (e.g., dashboards, tools, summaries) aligned with business workflows and stakeholder needs.
Drive adoption by ensuring stakeholders understand both what the data shows and how to act on it.
Establish initial patterns, standards, and best practices to enable repeatable and scalable DAM capabilities across the organization.
Partner with Operations, Finance, Industrial Engineering, and IT to align data solutions with business priorities and performance drivers.
Leverage external data and AI resources to accelerate development and delivery of solutions, while supporting long-term capability build within LSG.