Senior Data Engineer

about the role

RESPONSIBILITIES:

• Work with data to solve business problems, building and maintaining the infrastructure to answer questions and improve processes.
• Identify, design, and implement improvements to internal processes, including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
• Collaborate with internal customers to identify analytics requirements and design the best possible solution(s).
• Effectively partner with developers, operations across business functions, finance, HR, and others to communicate the results of the team's analytics insights, design tests, and incorporate recommendations into business processes.
• Use agile software development processes to make iterative improvements to our back-end systems.
• Model front-end and back-end data sources to help gain a more comprehensive picture of user flows across the system and enable powerful data analysis.
• Create data pipelines that cleanse, transform, and aggregate data from disparate sources.
• Create analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics.
• Develop models that can be used to make predictions and answer questions for the business as a whole.
• Explore ways to improve data quality and reliability.
• Work with business leaders to develop innovative advanced analytics products that enhance the customer experience, capitalize on growth opportunities, provide competitive advantages, and improve decision-making.
• Develop presentations for management, both within and outside the department, to communicate findings, interpret data analysis, and make recommendations based on the results.
• Develop content and train team members and end users on technical aspects, reports, and dashboards.
• Act as a liaison in Business Intelligence and Data Analytics initiatives between business users and the technical team. Work with stakeholders, including executive, product, data, and design teams, to support their data infrastructure needs, providing assistance with data-related technical issues.
• Partial project management operations to lead all aspects of projects, including: understanding stakeholder business requirements, independently formulating the analysis approach and hypothesis generation, identifying required data, preparing data for analysis, testing hypotheses, performing analyses, presenting complex information to multiple audiences in simplified terms, and identifying next steps and future opportunities.
• Process sensitive data and information according to guidelines.
• Be an advocate for best practices and continuous learning.