Director of Data Engineering

We are seeking an experienced and visionary Director of Data Engineering to lead our data strategy, architecture, and infrastructure. In this critical leadership role, you will oversee the design, development, and evolution of our modern data platform, from real-time streaming pipelines to scalable data warehouse and lake architectures. You will partner closely with Product, Engineering, and Analytics to ensure reliable, high-quality data powers analytics, reporting, experimentation, and machine learning across the organization.

What You Will Do

• Lead, mentor, and grow a team of data engineers and database administrators, fostering a culture of collaboration, accountability, and continuous improvement.
• Own the end-to-end design, development, maintenance, and migration of scalable ETL/ELT pipelines and data systems.
• Define and implement modern data architecture strategies, including data warehousing (e.g., Snowflake, BigQuery), data lakes, and real-time streaming pipelines.
• Establish best practices for data reliability, including monitoring, alerting, incident response, and data quality validation.
• Integrate and manage data from analytics platforms (including Google Analytics 4 / GA4) to support comprehensive reporting and insights.
• Partner with Analytics to enable self-service BI using tools such as Looker, including well-modeled, trusted datasets.
• Collaborate with Product and Engineering to ensure accurate instrumentation and reporting for A/B tests and experimentation.
• Communicate effectively with stakeholders to align data priorities with business goals and ensure the timely delivery of high-impact initiatives.

Who You Are

• 8+ years of experience in data engineering, including 2+ years leading teams or managing engineering functions.
• Strong experience with cloud data platforms (AWS preferred) and modern big data technologies.
• Advanced SQL skills for designing, querying, and optimizing relational databases and large datasets.
• Proven ability to lead and grow teams, with strong stakeholder management and communication skills.
• Deep experience with data warehousing (e.g., Snowflake, BigQuery) and data lake architectures.
• Strong proficiency with Python and familiarity with distributed compute frameworks such as Spark.
• Experience with orchestration frameworks such as Apache Airflow, Dagster, or similar.
• Experience enabling BI and analytics teams through tools like Looker, Tableau, or Power BI.
• Hands-on experience with dbt for transformation, modeling, and scalable analytics engineering patterns.

Nice to Have

• Experience leading teams in an Agile environment, including sprint planning, delivery execution, and cross-functional coordination.