wpromote - Senior Director, Data Engineering & Business Intelligence
Requirements
• 12+ years of experience in data engineering, BI, or analytics within an advertising agency environment (preferred) and/or client (Brand) environment • Experience working with marketing, sales, or digital media data (Google, Adobe, Meta, Salesforce, etc.) • Background in digital analytics platforms (e.g., Google Analytics, Adobe Analytics) • 5+ years in a leadership or management role • Proven experience building scalable data pipelines and modeling data using SQL and tools like dbt or similar • Expertise in cloud data platforms (e.g., BigQuery, Snowflake, Redshift) and orchestration tools (e.g., Airflow, Cloud Composer) • Strong understanding of ETL/ELT workflows and data warehousing best practices • Hands-on experience integrating with APIs and managing large-scale data ingestion • Deep familiarity with BI platforms such as Looker, Tableau, Power BI, or similar • Excellent communication and stakeholder management skills, including the ability to translate business needs into technical solutions • Demonstrated experience in implementing and maintaining rigorous data QA and governance processes • An understanding of modern data architecture patterns (e.g., event streaming, data lakehouses) • Experience in deploying predictive analytics and AI models into engineering and reporting workflows • Intermediate to advanced experience in Python/ R • Familiarity with conversational analytics, natural language interfaces, or chatbot integration for BI • Familiarity with project management tools such as JIRA, Asana, or Monday.com • Prior experience in a consulting environment, especially in marketing or technology services
Responsibilities
• Leading and mentoring a team of data engineers, business intelligence engineers, and reporting solution engineers to build and maintain accurate, dependable, and automated data pipelines and data models • Overseeing the architecture and design of our BI ecosystem across internal and client-facing environments while remaining hands-on in the design and development of client-facing solutions • Driving innovation by exploring new APIs, data providers, and integration approaches to expand our data capabilities • Serving as a coach-player across client work, guiding technical approach and best practices while directly contributing to pipeline development, data modeling, QA, troubleshooting, and delivery • Partnering with analytics, strategy, and engineering stakeholders to define and deliver on data and reporting requirements • Designing scalable and reusable data models using dbt and BigQuery, optimized for reporting, forecasting, analytics, and client-specific customization • Leading the development of modern reporting interfaces and conversational analytics tools that empower users to self-serve insights • Evolving and enforcing QA processes, data governance standards, documentation practices, and engineering best practices to improve reliability and consistency across client deliverables • Leading data modernization by utilizing AI-assisted workflows and automation to manage client deliverables efficiently and effectively • Managing stakeholder expectations, project timelines, prioritization, and technical tradeoffs for cross-functional data initiatives while ensuring high-quality execution on active client work
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT