Manager, Software Engineering – BI & Analytics

Job Summary

We are seeking a Manager, Software Engineering, focused on BI & Analytics to lead a high-performing, multidisciplinary team in building and maintaining the data pipelines, AI-powered data solutions, and custom analytics UIs and dashboards that are foundational to Disney’s Ad Platforms. In this role, you’ll manage both frontend and backend software & data engineering, ensuring that business and end-user needs are met with reliability, scalability, and outstanding UI/UX design.

• Instill a culture grounded in engineering best practices such as code quality, documentation, automation, and continuous improvement.
• Ensure engineering principles are consistently applied across projects and teams.
• Manage, mentor, and grow a team of high-performing software and data engineers, fostering a collaborative and innovative culture.
• Coordinate with Product Management to align engineering roadmaps with product initiatives and timelines.
• Partner with Program Managers to drive planning, prioritization, and delivery of cross-functional efforts.
• Collaborate with QA leadership to build data quality processes and end-to-end validation.
• Lead and grow a high-performing team of software and data engineers working on mission-critical data products.
• Set engineering roadmaps, delivery timelines, and platform-level initiatives.
• Drive adoption of best-in-class tools and practices for data governance, lineage, observability, and cost optimization.
• Provide technical guidance and career development for the team.
• Collaborate with senior leadership to define data strategy and long-term architecture vision.
• Manage capacity planning, resource allocation, and performance reviews.
• Lead vendor/tool evaluations and oversee key integration efforts.
• Partner with BI and analytics leads to ensure consistent, reliable data is delivered across the enterprise.
• Spearhead the implementation of custom dashboards and analytics UIs, leveraging modern web frameworks (React, Angular, Vue, etc.), advanced data visualization, and design system best practices.
• Rapidly prototype UI components tailored to stakeholder/business requirements, ensuring high standards for usability, accessibility, and visual polish.
• Drive the integration of AI/ML solutions into both backend pipelines and analytics products; champion the use of AI-powered software development processes and robust, end-to-end SDLC practices.

• Languages:
  
  Scala, Python, SQL, JavaScript.
• Data Processing:
  Apache Spark, Flink, Airflow.
• Platforms & Tools:
  Databricks, Hive, Presto, Snowflake.
• Cloud: AWS (S3, EMR, Glue, Lambda).
• Minimum of 8 years of relevant software engineering, data engineering or data science – preferably with a digital media or digital advertising company.
• Experience delivering products in an agile software development environment including sprint work in Jira.
• Excellent interpersonal skills with the ability to collaborate and partner across multiple teams and organizations.
• Strong SQL experience including writing/optimizing complex queries against distributed data stores such as Aurora, Hadoop, Hive, Oracle, and Snowflake.
• Experience with data pipeline and workflow management tools:
  Apache NiFi or Apache Airflow.
• Expert level knowledge in at least one programming language such as Python, R, Scala, Java.
• Demonstrated experience working with business intelligence tools such as Micro Strategy, Tableau, Business Objects, Looker, etc.
• Strong experience building and deploying dashboards and UIs with frameworks such as React, Angular, or Vue.
• Demonstrated ability to quickly prototype and implement custom UI components to meet evolving business/stakeholder specs.
• Familiarity with AI-powered solution development and integrating machine learning into production data/analytics environments.
• Strong software development life cycle (SDLC) management experience, including source control, CI/CD, and agile workflows (Jira).
• Demonstrated ability to effectively communicate complex concepts to technical and unacquainted audiences.
• Experience in working with large datasets (Terabytes or more).
• Strong presentation and documentation skills including experience working with Confluence,…