Director, Head of Data Engineering

Affiliated Monitoring•Union, NJ

64d

About The Position

Affiliated Monitoring is seeking a visionary and hands-on Director, Head of Data Engineering to lead the evolution of our enterprise data capabilities. This is a critical leadership position responsible for architecting and implementing a modern data infrastructure—including our first enterprise data warehouse—to support our rapidly expanding needs in business intelligence, AI, and operational reporting. Our systems produce vast amounts of transactional data, which remain underutilized. You will spearhead the transformation of our data environment into a strategic asset—one that not only empowers decision-making but also fuels the next generation of AI-driven innovation. This role is both strategic and technical. You will start as a player-coach (approximately 50% hands-on), evolving into a leadership-heavy role (up to 75%) as you scale the team and build a future-ready data organization. If you're excited about the prospect of shaping a data strategy from the ground up, enabling machine learning and AI, and building a high-performance team, this is the opportunity for you.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred)
Proven success in leading data teams and scaling data infrastructure
Hands-on expertise with modern data stacks (Snowflake, dbt, Airflow, AWS, Looker, etc.)
Experience delivering enterprise data platforms that power internal analytics, external products, and AI/ML use cases
Strong business acumen; able to translate technical vision into business impact
Excellent leadership, project management, and communication skills
Demonstrated ability to work cross-functionally and influence at all levels

Responsibilities

Design and implement a modern, scalable enterprise data warehouse from the ground up
Lead the development of a unified data architecture that supports operational reporting, business intelligence, and AI readiness
Evaluate and select data platforms, tools, and technologies (e.g., Snowflake, dbt, Airflow) that support current needs and future innovation
Partner with Engineering, Product, and Business stakeholders to understand data requirements and translate them into actionable architecture and pipelines
Advance our ability to deliver self-service analytics across the organization
Build and mentor a high-performing data team; foster a collaborative, agile, and innovation-driven culture
Implement robust data governance, quality assurance, and security practices
Develop and execute a strategy to support machine learning, natural language processing, and other AI use cases
Stay informed on emerging trends in data engineering and AI, and integrate best practices into our roadmap
Ensure data initiatives are delivered on time, within budget, and aligned with business goals