Director, Data Engineering
About The Position
Horizon Media, founded in 1989 by Bill Koenigsberg, is recognized as one of the most innovative marketing and advertising firms. We are headquartered in New York City, with offices in Los Angeles and Toronto. A leader in driving business solutions for marketers, Horizon is known for its highly personal approach to client service. Renowned for its incredible culture, Horizon is consistently named to all the prestigious annual Best Places to Work lists published by Fortune, AdAge, Crain’s New York Business and Los Angeles Business Journal. Together we are building a place of belonging. At Horizon, we understand the value that different perspectives can bring to our clients and culture, so we strive for an environment where our employees feel welcomed, safe and empowered. We value YOU and believe that your authentic voice and unique perspective allows us to create a more rewarding culture, and experience, together. Our simple recipe for success? We hire talented people (thinkers, doers, dreamers, makers), challenge them and give them every opportunity to grow. As a Director Data Engineering, you will be responsible for leading the design and implementation of enterprise-wide analytics solutions that transform raw data into actionable business insights. This role combines deep expertise in data architecture, visualization development, and analytics engineering to create scalable solutions that enable data-driven decision-making across the organization. You will establish standards for data transformation, testing, and documentation while partnering with leadership to align analytics initiatives with business objectives.
Requirements
- Bachelor’s degree in computer science, Statistics, Mathematics, or related field
- 8+ years of experience in analytics, data engineering, or related field
- Strong experience with cloud data warehouses (e.g., Snowflake, Google BigQuery, AWS Redshift).
- Solid experience with big data technologies (e.g., Spark, Hadoop, Kafka).
- Advanced proficiency in SQL and one or more programming languages (e.g., Python, Scala).
- Experience with orchestration tools such as Airflow, dbt, or similar.
- Hands-on experience with cloud platforms like AWS, GCP, or Azure.
- Knowledge of data modeling (star/snowflake schema), partitioning, and optimization strategies.
- Proven experience leading and mentoring technical teams including offshore resources.
- Advanced dbt experience with expertise in: Package development and dependency management Custom macro development Testing framework implementation CI/CD pipeline integration
- Expert-level knowledge of data modeling, dimensional design, and analytics engineering best practices
- Excellence in stakeholder management and technical communication
- Track record of successfully delivering enterprise-scale solutions
- Minimum 3 years of experience with Snowflake, including: Performance optimization and query tuning Security and access control implementation Resource monitoring and cost optimization Data warehouse architecture design
Nice To Haves
- Prior experience with marketing and advertising data
- Experience with Streamlit for building data visualizations & applications
- Knowledge of other modern data visualization frameworks (D3.js, Plotly, etc.)
- Familiarity with machine learning visualization techniques
- Building pipelines in support of AI applications
- Publishing applications to Snowflake’s marketplace
Responsibilities
- Design and Implement Enterprise Analytics leveraging LLMs/Gen AI
- Architect and oversee implementation of enterprise-wide data modeling strategies in Snowflake
- Define and maintain dbt modeling standards and best practices across the organization
- Design scalable solutions for complex analytical problems spanning multiple data domains
- Lead the development and implementation of reusable analytics frameworks and components
- Drive implementation of advanced performance optimization strategies for large-scale data transformations
- Partner with leadership to align analytics initiatives with business objectives
- Drive adoption of modern engineering tools with emphasis on dbt development practices
- Establish best practices for engineering across the organization
- Evaluate and recommend new technologies and approaches to improve capabilities
- Lead technical discussions and decision-making with executives, bridging engineering teams and stakeholders
- Lead and manage a hybrid data engineering team composed of full-time employees and contractors. Coordinating work across onshore, near-shore and offshore resources to ensure consistent delivery, quality standards, and effective collaboration across time zones.
- Mentor and guide junior analytics engineers in dbt development and analytics engineering best practices
- Review and approve technical designs and perform code reviews
- Foster a culture of innovation and continuous improvement within the team
- Lead knowledge sharing initiatives and internal training programs
Benefits
- health insurance coverage
- life and disability insurance
- retirement savings plans
- company paid holidays and unlimited paid time off (PTO)
- mental health and wellness resources
- pet insurance
- childcare resources
- identity theft insurance
- fertility assistance programs
- fitness reimbursement
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What This Job Offers
Job Type
Full-time
Career Level
Director
