Senior Manager, Business Intelligence Data Engineering

Senior Manager, Business Intelligence & Data Engineering The Senior Manager, Business Intelligence & Data Engineering is responsible for architecting, building, and scaling the Nationals’ end‑to‑end data ecosystem to support strategic decision‑making across the organization. This role combines data engineering, analytics, and data science, with ownership of core data products including forecasting models, reporting infrastructure, and business intelligence tools. This individual will lead the design and development of scalable data pipelines, data models, and machine learning solutions that power revenue‑driving functions such as ticket sales, marketing performance, financial planning, and customer retention. The role requires close collaboration with cross‑functional stakeholders across Sales, Marketing, Finance, IT, Ticket Operations, and Partnerships to ensure data is effectively ingested, transformed, and delivered in actionable formats. The Nationals are a military‑friendly organization actively recruiting veterans and spouses. Essential Duties and Responsibilities Data Engineering & Architecture Design, build, and maintain scalable data pipelines and ELT workflows using Terraform, Google Cloud Platform, BigQuery, dbt, and Airflow. Own the architecture and optimization of the Nationals’ cloud‑based data warehouse and data lake. Ingest and integrate data from key systems including ticketing, CRM, point‑of‑sale, marketing platforms, and MLB data sources. Ensure data quality, governance, testing, and documentation across all pipelines and datasets. Manage and optimize cloud infrastructure performance and cost efficiency. Business Intelligence & Reporting Develop and maintain dashboards and reporting solutions in Tableau to support business operations and executive decision‑making. Partner with stakeholders to translate business requirements into scalable data models and intuitive visualizations. Enable near real‑time reporting across revenue streams and operational metrics. Support financial and operational reporting needs, including budgeting and forecasting workflows. Data Science & Machine Learning Own and enhance predictive models for: Attendance forecasting Ticket sales and revenue forecasting Customer segmentation and retention Apply statistical and machine learning techniques using Python. Productionize models within the data platform and ensure ongoing monitoring, evaluation, and improvement. Partner with leadership to translate model outputs into actionable business strategies. Cross‑Functional Collaboration Collaborate with Sales, Marketing, Finance, IT, Ticket Operations, and Partnerships to identify opportunities and deliver data‑driven solutions. Act as a strategic partner in defining KPIs, measurement frameworks, and experimentation strategies. Work with MLB and external vendors on data integrations and platform enhancements. Leadership & Team Development Manage and mentor the Analyst, Business Data Systems. Establish best practices in data engineering, analytics, and data science workflows. Foster a high‑performing, innovative data culture within Business Strategy & Analytics. Compensation The projected wage range for this position is $115,000 to $125,000 per year. Actual pay is based on several factors, including but not limited to the applicant’s qualifications, skills, expertise, education/training, certifications, and other organization requirements. Starting salaries for new employees are frequently not at the top of the applicable salary range. Experience Required Office: Working conditions are normal for an office environment. Position will require some weekend and/or evening work. Utmost standards of integrity in all business dealings. Excellent communication skills and ability to tailor key messages to the appropriate audience. Knowledge of P&L structures and levers to optimize revenues and costs, especially in dynamic consumer markets. Strong understanding of data modeling, ETL/ELT design, and data architecture best practices. Experience with machine learning frameworks and statistical modeling techniques. Solid Excel skills (pivot tables, data analysis, financial modeling support). Tableau or similar BI tools. Terraform (infrastructure as code). Apache Airflow (workflow orchestration). dbt (data transformation, testing, documentation). BigQuery (data warehousing). Google Cloud Platform (GCP). Expert‑level proficiency in SQL and Python. Experience building elegant data visualizations from relational databases. Proven track record of collecting and understanding complex requirements and delivering creative and effective solutions to the business. Professional experience in data engineering for at least 4 years. Preferred Experience working with ticketing, CRM, or transactional datasets strongly preferred. Experience in sports, entertainment, or similar consumer‑driven industries. Professional experience in analytics, business intelligence, and data science for at least 4 years. Education (Preferred) Bachelors or better in Computer Science or related field. Behaviors Required Detail Oriented: Capable of carrying out a given task with all details necessary to get the task done well. Functional Expert: Considered a thought leader on a subject. Motivations Required Entrepreneurial Spirit: Inspired to perform well by an ability to drive new ventures within the business. Self‑Starter: Inspired to perform without outside help. Equal Opportunity Employer This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor. #J-18808-Ljbffr Washington Nationals