Head of Data Engineering

İşin təsviri

Job responsibilities:

• Designing and developing robust and scalable data architectures.
• Planning and implementing data warehousing solutions and data lakes.
• Building and maintaining reliable and efficient data pipelines.
• Implementing ETL (Extract, Transform, Load) processes for data integration and workflow automation.
• Overseeing the management of SQL and NoSQL databases.
• Ensuring high availability, disaster recovery, and efficient data storage solutions.
• Utilizing big data technologies (like Hadoop, Spark) for handling large-scale data processing.
• Integrating machine learning algorithms and analytics tools as needed.
• Monitoring system performance and conducting regular tuning to optimize data processing.
• Implementing data caching, indexing, and other strategies to enhance data processing and storage.
• Establishing data quality standards and processes.
• Implementing tools and practices to ensure data accuracy and consistency.
• Enforcing data security measures and ensuring compliance with data protection regulations.
• Implementing access controls and data encryption where necessary.
• Leveraging cloud services for scalable data storage and computing.
• Ensuring adherence to data governance policies and practices.
• Overseeing data quality and ensuring compliance with data privacy regulations.

Job requirements:

Educational Background:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Advanced degrees or certifications in data engineering, big data technologies, or cloud computing are highly desirable.

Technical Expertise:

• Experience in data engineering, including designing and building scalable data architectures.
• Proficiency in database management, both SQL and NoSQL databases.
• Expertise in big data technologies (e.g., Hadoop, Spark).
• Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud Platform) for data solutions is a plus
• Strong knowledge of ETL processes and data pipeline construction.
• Familiarity with data modeling, data warehousing, and data lakes.

Programming Skills:

• Strong programming skills in languages like Python (or Java or Scala).
• Experience with SQL for complex querying and data manipulation.

Data Security and Compliance Knowledge:

• Understanding of data security best practices, including encryption and secure data handling.

Experience:

• Several years of experience in a data engineering role with progressive responsibilities.
• Prior experience in a leadership or management role, overseeing a technical team.

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