• Meet and coordinate with internal and external stakeholders to establish project scope, system goals, and requirements • Help translate business requirements into technical specifications for data consumption and use • Provide guidance on appropriate data platform(s) (repository, database, etc.) to meet requirements • Accurately map data attributes between different domain models • Develop, analyze, prioritize, and organize requirement specifications, data mapping, diagrams, data models and flowcharts for developers and testers to follow • Help deploy and troubleshoot application data pipelines across various architectural environments that will vary by client from legacy to modern including application servers, queues, API gateways, databases, etc. or cloud-based equivalents

• Own the operational health, architecture intelligence, and cost optimization of cloud environments • Develop and maintain technical understanding of the organization’s cloud architecture • Map relationship between architectural decisions and cost drivers • Identify cost anomalies, inefficiencies, and optimization opportunities • Build and maintain dashboards for real-time visibility into cloud cost trends • Help define and enforce cloud governance policies • Serve as primary point of contact for cloud cost and operations questions

Role Description The Senior Manager, Data Engineering will play a critical role in revitalizing OTG’s data analytics platform and strategy, transforming how data is leveraged across operations, finance, and guest experience. This role will serve as a hands-on leader responsible for building and modernizing OTG’s data platform, driving scalable data solutions, and enabling real-time insights that power business decisions across the organization. This individual will help define the future state of OTG’s data ecosystem, ensuring it supports growth, operational efficiency, and innovation. - Lead the design and execution of a modern data platform strategy, aligned with OTG’s business goals and growth trajectory. - Drive the revitalization and modernization of data pipelines, data models, and data infrastructure. - Build and optimize scalable ETL/ELT pipelines to support high-volume transactional data from POS, operations, and customer systems. - Establish a roadmap for data architecture, data governance, and analytics enablement. - Ensure data systems support real-time insights, operational reporting, and advanced analytics use cases. - Partner with Engineering, Product, Finance, and Operations teams to translate business needs into data-driven solutions. - Define and enforce data engineering standards, best practices, and governance frameworks across the organization. - Lead the migration and modernization of legacy data systems into cloud-based platforms. - Oversee data quality, data integrity, and system reliability across the enterprise. - Manage and mentor a team of data engineers, driving performance, accountability, and growth. - Provide hands-on technical leadership, including coding, troubleshooting, and architectural design as needed. - Collaborate with external vendors and partners to support delivery and scalability initiatives. Qualifications - Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience). - 6–10+ years of experience in data engineering, data architecture, or related technical roles. - 2–4+ years of leadership experience, managing engineering teams or technical initiatives. - Proven experience building and scaling modern data platforms in cloud environments (AWS, Azure, or GCP). - Strong background working in high-volume, data-intensive environments (hospitality, retail, QSR, or similar preferred). Requirements - Data Platform Modernization & Transformation. - Data Engineering & ETL/ELT Pipeline Development. - Cloud Data Architecture (Snowflake, Databricks, Redshift, Synapse, etc.). - Real-Time Data & Streaming (Kafka or similar). - Data Governance & Data Quality Management. - Cross-Functional Stakeholder Collaboration. - Hands-On Technical Leadership. - Team Leadership & Talent Development. - Problem Solving & Continuous Improvement. - Communication & Organizational Agility. Company Description On the Go (OTG) has elevated the dining and retail experience for travelers by bringing together world-class hospitality, award-winning dining concepts, and forward-thinking technology. With more than 300 unique dining and retail locations across North America’s busiest airports, we’re fueled by a passion for creating exceptional guest experiences—made possible every day by our incredible Crewmembers. At OTG, people truly come first. We invest in our teams and foster growth in an exciting, fast-paced environment where everyone can shine. How we work is just as meaningful as what we accomplish. Our values—Care, Continuous Improvement, Quality, and Teamwork—guide the way we show up for our guests and for each other. We are committed to fostering an inclusive, safe, and dynamic workplace where individuals feel empowered to contribute and grow.

• Build and own data marts spanning operational, advertising, and telemetry data — designed for analytics, reporting, AI, and operational use cases • Ingest and process large-volume event data from client apps, ad tech platforms, stitcher services, ad servers, and telemetry pipelines • Clean, harmonize, and integrate data across systems with different schemas, identifiers, grains, and timing — producing conformed dimensions and shared definitions (users, sessions, devices, content, campaigns, impressions) • Stitch identity and sessions across client, server, and ad-side events to enable accurate user, content, and revenue analytics • Troubleshoot data incidents end-to-end — from a dashboard anomaly back through marts, transformations, and raw event logs — and drive permanent fixes • Build, support and improve visualizations in partnership with analysts and stakeholders, ensuring dashboards are accurate, performant, and trusted • Establish data quality standards — testing, monitoring, alerting, freshness and volume SLAs — so issues are caught before stakeholders see them • Document datasets, lineage, and business logic so consumers across analytics, product, and ad ops can self-serve with confidence • Partner closely with analysts, data scientists, ad ops, product, and source-system owners to translate business questions into durable data models • Develop/Improve new or underutilized data sets internally and externally • Analyze complex and huge datasets to o understand patterns and develop actionable insights o develop new initiatives to improve business KPIs such as usage, revenue, etc. o define new metrics and KPIs to track new initiatives • Work closely with all business functions to enable transparent data-based decision making. • Contribute to the daily variance identification across multiple platforms. • Drive complex strategic projects investigations and analysis. • Work cross functionally on enterprise-wide programs with Engineering, Broadcast Operations, Finance, BI and Data Engineering teams to improve performance and profitability. • Research and share information on the latest tools and best practices. • Mentor engineers and analysts on SQL, modeling, event data, and engineering best practices.