Senior Director, Data Engineering
Remote (US)Full-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 10+ years of experience in data engineering, with at least 5 years in a leadership role
- Required Skills
- AWSSQLETLGCPHadoopKafkaAzureNosqlSpark
Requirements
- BS or MS in Computer Science, Data Engineering, or a related field
- 10+ years of experience in data engineering
- At least 5 years in a leadership role
- Proven track record of designing and managing large-scale, distributed data systems
- Deep expertise in data engineering technologies such as Hadoop, Spark, Kafka
- Expertise in cloud platforms (AWS, Azure, GCP)
- Strong knowledge of database systems (SQL and NoSQL)
- Strong knowledge of ETL processes
- Excellent leadership and communication skills
- Ability to influence across all levels of the organization
- Experience with data governance, compliance, and best practices
Responsibilities
- Lead, mentor, and grow a team of skilled data engineers, fostering a culture of collaboration, innovation, and excellence.
- Attract and retain top talent to build a world-class Data Engineering organization.
- Oversee the development and optimization of scalable, reliable, and efficient data pipelines and platforms.
- Ensure data systems are designed for high availability, security, and performance.
- Partner with Product, Data Science, Engineering, and Business teams to understand their data needs and deliver solutions that meet those needs.
- Act as a key liaison between technical teams and business stakeholders, ensuring alignment and transparency.
- Stay abreast of emerging technologies and industry best practices in data engineering.
- Drive the adoption of new tools, technologies, and methodologies to enhance the team’s efficiency and effectiveness.
- Define and enforce standards, processes, and best practices for data engineering.
- Monitor and optimize the performance of data systems to ensure they meet SLAs and business requirements.
- Ensure that all data systems and processes comply with relevant regulations and standards.
- Implement robust data governance practices to maintain data quality and integrity.
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