Director of Data Engineering

Our client is a Series A funded SaaS startup specializing in Threat Intelligence. They leverage advanced machine learning for narrative intelligence, helping enterprises and government agencies combat social media manipulation and emerging narrative threats. Their platform processes vast amounts of unstructured, cross-channel media data, converting it into actionable insights. They are looking for a Director of Data Engineering expert to spearhead their development, implementation, and advancement of their data infrastructure. In this role, you will work closely with the Data, Product, and Engineering team. Will be tasked with managing 2 people initially then scale into consolidated Data team whilst you will be reporting into the VP of Engineering. Key Responsibilities: Develop and implement a long-term vision for data engineering and DevOps strategies. Collaborate with senior leadership to prioritize initiatives, set objectives, and define measurable outcomes. Build, mentor, and lead a diverse team of Data Engineers Oversee the design, development, and maintenance of scalable data pipelines, warehouses, and processing frameworks. Lead adoption of modern DevOps methodologies to streamline CI/CD pipelines and deployment processes. Partner with cross-functional teams, including product, analytics, and engineering, to align technical solutions with business needs. Present project updates, performance metrics, and strategic initiatives to leadership. Required Qualifications: 10 years of engineering experience, with at least 5 years in data engineering Proven experience in designing and implementing data architectures, ETL processes, and DevOps pipelines. Expertise in cloud platforms AWS, Azure, or GCP. Preferably AWS Experience with modern DevOps tools such as Kubernetes, Docker, Terraform, Jenkins, or similar. Track record of successfully managing and scaling high-performing technical teams. Experience with data orchestration platforms such as Dagster or Airflow. Strong database architecture design skills for both structured and unstructured data. Advanced knowledge of Elasticsearch or OpenSearch, including configuration and search functionalities. Ability to define and communicate data architecture requirements while staying up to date with best practices.