Senior Data Engineer

Key responsibilities

• Implement ETL systems that are operationally stable, efficient, and automated.
• This includes technical solutions that are scalable, aligned with the enterprise architecture and can adapt to changes in business.
• Monitor and optimize batch jobs, including automation and scheduling.
• Consistently review and enhance performance with key focus on ease of maintenance & jobs reusability.
• Work closely with internal/external teams devise requirements of data integrations, specific to Data Warehouse/Data Marts implementation
• Provide data quality and volume metric measurement across organization data.
• Implement best practices to data change management, documentation, and data protocols.
• Growing the capabilities of the data platforms, solving new data problems and challenges.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Work with stakeholders including the Business Analysts and Data Scientists teams to assist with data-related technical issues and support their data infrastructure needs.
• Support and implement initiatives for continual engineering improvements.
• Review business and technical requirements and ensure the data integration platform meets requirements.
• Apply industry best practices for ETL design and development.
• Produce written deliverables for technical design, system testing and implementation activities.
• Conduct System Testing – execute job flows, investigate system defects, resolve defects and document results.
• Work with DBAs, application specialists and technical services to tune performance of the ETL system to meet performance standards and SLAs.
• Assist in the development, documentation and application of best practices and procedures.