Director of Data Engineering

Director of Data Engineering

Requirements

• 10+ years of experience in Data Engineering or a related field, with at least 4 years in engineering management leading high-performing teams.
• Demonstrated expertise in developing and maintaining scalable, reliable, and high-quality data products and pipelines that support business-critical analytics, experimentation, and AI/ML workloads.
• Experienced at building and managing data pipelines that hydrate online ML features.
• Deep expertise with modern data engineering technologies, including Kafka, Spark, dbt, Airflow, Databricks, and cloud-based data platforms (AWS, GCP, or Azure).
• Strong familiarity with modern cloud-native architectures and infrastructure, ensuring efficient, secure, and cost-effective data solutions.
• Strategic technical leadership with a proven ability to align data engineering strategies with product and business objectives, driving initiatives that exceed business goals.
• Passion for developing, coaching, and scaling high-performing teams, fostering a culture of growth, inclusivity, and operational excellence.
• Exceptional communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders, ensuring clarity and alignment across teams.
• Highly motivated, proactive and collaborative team player with the ability to persuade others and influence outcomes.

Responsibilities

• Play a key role on the Data Leadership Team, shaping Hinge’s overall data strategy while setting and executing the Data Engineering strategy.
• Ensure strategic alignment with Hinge’s broader business, product, and technology objectives, driving data-driven innovation across the company.
• Enable Hinge’s AI and machine learning initiatives by building and optimizing high-quality, scalable, and reliable data pipelines.
• Transform the current existing data engineering practices into unified and streamlined standards that enable optimized, high quality, scalable, and reliable data pipelines.
• Lead, scale, and mentor a high-performing team of data engineers and data engineering managers, fostering a culture of growth, collaboration, innovation, and operational excellence.
• Drive technical excellence, upholding high standards for code quality, system design, scalability, and reliability across all data engineering initiatives.
• Provide hands-on technical leadership, actively participating in architecture reviews, design discussions, and guiding critical technical decisions.
• Collaborate cross-functionally with BI Engineers, Backend and Client Engineers, ML Engineers, Data Scientists, and Product Managers to develop and implement scalable, data-driven solutions that power analytics, experimentation, and machine learning.
• Ensure seamless data integration across Hinge’s products, features, and systems, enabling a unified, high-quality data ecosystem.
• Define and implement best practices that enhance team efficiency, optimize workflows, and drive continuous improvement in data engineering operations.
• Stay ahead of industry trends and emerging technologies, driving innovation in data engineering to support Hinge’s evolving business needs.

Preferred Qualifications

No preferred qualifications provided.