Director, Data Engineering

Horizon Media•New York, NY

1d•Hybrid

About The Position

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