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Senior/Lead Analytics Data Engineer
hace 2 meses
We are seeking a highly skilled Senior/Lead Analytics Data Engineer to join our team at Agileengine, LLC. As a key member of our data engineering team, you will play a critical role in designing, developing, and maintaining our data infrastructure to support business intelligence and analytics needs.
Key Responsibilities- Data Modeling and Design: Develop and maintain data models (conceptual, logical, and physical) to support analytics and reporting needs.
- Data Dictionary and Schema Management: Create and manage data dictionaries, ER diagrams, and schema designs that align with business requirements.
- Collaboration and Standards: Collaborate with data architects and stakeholders to define data modeling standards and best practices.
- Technical Expertise: Utilize code (SQL, Python, etc.) and apply engineering, reporting, and visualization expertise to solve business problems.
- Team Leadership: Develop and lead a team of junior data analysts, providing mentorship, training, and coaching to increase technical acumen across the team.
- System Development: Develop scalable systems to expand reporting capabilities, facilitate ad hoc analysis, and improve data-driven decision-making at all levels of the business.
- Complex Data Analysis: Work with large, complex data sets. Solve difficult data transformation problems with efficiency, applying advanced analytical methods as needed.
- Analysis and Presentations: Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Code Standards and Testing: Contribute to the establishment of standards for writing clean, organized code and documentation to streamline data and analytics workflow.
- Culture and User Experience: Drive and promote a culture of testing, observability, and scalability with a data-driven mindset. Manage and continuously improve business user's experience with data and reporting, including KPI development, data visualization, and communication of applicable insights to audiences at varying levels of technical sophistication.
- Data Literacy and Partnerships: Increase overall data literacy across ELC through education and advocacy. Develop partnerships with engineering, data science, and product teams to deliver on major cross-functional reporting, measurement, and testing efforts.
- Education: BS/BA in a quantitative field; a plus if MS degree in a quantitative discipline (e.g., Computer Science, Mathematics, Statistics).
