Senior Director, Data Engineering
United StatesFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 10+ years of experience in data engineering, software engineering, or data platform development in enterprise environments. 5+ years of experience in a senior leadership role managing data engineering or platform teams.
- Required Skills
- AWSSQLArtificial IntelligenceETLGCPHadoopKafkaMachine LearningAzureNosqlSpark
Requirements
- 10+ years of experience in data engineering, software engineering, or data platform development in enterprise environments
- 5+ years of experience in a senior leadership role managing data engineering or platform teams
- Strong expertise in building and scaling distributed data systems using tools such as Spark, Hadoop, Kafka, and cloud platforms (AWS, Azure, or GCP)
- Deep knowledge of SQL and NoSQL databases, ETL/ELT pipelines, and modern data architecture patterns
- Proven experience designing data platforms that support analytics, machine learning, and AI-driven use cases
- Strong understanding of data governance, security, compliance, and data quality frameworks
- Experience collaborating across technical and non-technical stakeholders in complex, fast-paced environments
- Excellent communication and leadership skills with the ability to influence at executive level
- Hands-on mindset with a passion for scalable, high-performance data systems and innovation
Responsibilities
- Lead the strategy, execution, and scaling of enterprise-grade data engineering systems that support analytics, AI, and data product initiatives across the organization
- Define and execute the long-term vision and roadmap for data engineering, aligned with business and product strategy
- Lead, mentor, and grow a high-performing data engineering team, fostering technical excellence, innovation, and collaboration
- Architect and oversee scalable data pipelines, platforms, and distributed systems supporting large-scale data processing
- Ensure data infrastructure is reliable, secure, high-performing, and optimized for availability and scalability
- Partner with product, engineering, data science, and business stakeholders to deliver end-to-end data solutions
- Establish data engineering standards, best practices, and governance frameworks to ensure data quality and consistency
- Drive adoption of modern data technologies, cloud platforms, and advanced processing frameworks
- Oversee operational performance of data systems, ensuring compliance with SLAs and business requirements
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