Senior Director, Data Engineering & Business Intelligence
New
Remote, United StatesFull-TimeDirector
Salary140,000 - 195,000 USD per year
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Job Details
- Experience
- 12+ years of experience in data engineering, BI, or analytics
- Required Skills
- SQLBusiness IntelligenceETLData engineeringStakeholder managementBigQuerydbt
Requirements
- 12+ years of experience in data engineering, BI, or analytics
- Experience working with marketing, sales, or digital media data
- 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
- 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, or Power BI
- Excellent communication and stakeholder management skills
- Demonstrated experience in implementing and maintaining rigorous data QA and governance processes
- Experience in deploying predictive analytics and AI models into engineering and reporting workflows
Responsibilities
- Leading and mentoring a team of data engineers, business intelligence engineers, and reporting solution engineers
- Overseeing the architecture and design of our BI ecosystem across internal and client-facing environments
- Driving innovation by exploring new APIs, data providers, and integration approaches
- Serving as a coach-player, guiding technical approach and best practices
- Partnering with analytics, strategy, and engineering stakeholders to define and deliver data and reporting requirements
- Designing scalable and reusable data models using dbt and BigQuery
- Leading the development of modern reporting interfaces and conversational analytics tools
- Evolving and enforcing QA processes, data governance standards, and documentation practices
- Leading data modernization by utilizing AI-assisted workflows and automation
- Managing stakeholder expectations, project timelines, and technical tradeoffs
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