Director Data Engineering

We are seeking a visionary and technically adept Senior Data Engineering Leader to architect, scale, and optimize our data infrastructure. This role will drive the design and implementation of robust, cost-efficient, and observable data pipelines that power analytics, AI/ML, and operational systems across the enterprise. The ideal candidate will be a strategic thinker who can influence senior leadership and lead high-performing engineering teams.

Primary Responsibilities:

1. Data Pipeline Architecture: Design and implement scalable, high-performance data pipelines that support batch and real-time processing across diverse data domains
2. Total Cost of Ownership (TCO): Architect solutions with a focus on long-term sustainability, balancing performance, scalability, and cost efficiency
3. Operational Observability: Establish proactive monitoring, alerting, and logging frameworks to ensure system health, data quality, and SLA adherence
4. CI/CD & Automation: Champion automated testing, deployment, and release processes using modern DevOps practices. Ensure robust version control and rollback strategies
5. Blue-Green Deployments: Implement blue-green or canary deployment strategies to minimize downtime and risk during releases
6. Strategic Communication: Translate complex architectural decisions into business value. Confidently present and defend architectural choices to senior technology and business leaders
7. Leadership & Mentorship: Lead and mentor a team of data engineers, fostering a culture of innovation, accountability, and continuous improvement
8. Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

1. Undergraduate degree or equivalent experience
2. Proven experience leading enterprise-scale data engineering initiatives
3. Hands-on experience with CI/CD pipelines, infrastructure-as-code (e.g., Terraform), and containerization (e.g., Docker, Kubernetes)
4. Experience with data governance, privacy, and compliance frameworks
5. Experience with AI/ML data pipelines and MLOps practices
6. Experience in healthcare, finance, or any other regulated industries
7. Deep expertise in data architecture, distributed systems, and cloud-native technologies (e.g., AWS, GCP, Azure)
8. Solid command of data modeling, ETL/ELT, orchestration tools (e.g., Airflow, dbt), and streaming platforms (e.g., Kafka)
9. Demonstrated success in implementing observability frameworks (e.g., Prometheus, Grafana, Datadog)
10. Proven excellent communication and stakeholder management skills