Data Engineer at Smartsheet building data infrastructure for the Go-To Market organization. Collaborating with analytics teams to optimize sales performance and reporting capabilities.
Responsibilities
Help to create, evolve, and maintain the reporting infrastructure for the Sales organization to facilitate data across the organization
Partner with engineering, data science, and other analytics teams to build scalable analytics solutions with a focus on reporting capabilities
Mine large datasets to ensure data accuracy and completeness for reporting purposes
Analyze and monitor data for anomalies, with a focus on data quality and consistency within reports
Develop and maintain key performance indicators (KPIs) to track sales performance, pipeline health, and other critical metrics
Automate report generation and distribution to improve efficiency
Provide technical expertise and guidance to junior analysts on data extraction, transformation, and loading (ETL) processes and reporting best practices
Ensure data governance and data integrity across all reporting tools and platforms
Proactively identify and propose improvements to existing reporting processes and systems
Be a mentor and leader to the more junior analysts on the team
Perform other duties as assigned
Requirements
Bachelor's degree in a quantitative field (e.g. engineering, sciences, math, statistics, business, or economics)
5+ years of experience in an analytics/engineering role with increasing responsibility
Experience in Cloud and SaaS go-to-market (GTM)
Expertise in SQL and preparing data for analysis, modeling, and visualization
3+ years of experience using Python for data analysis / automation
3+ years of experience with dbt core
3+ years of experience with Git (Gitlab, Github etc.) and CI/CD concepts like branching, merging, Code Reviews
Demonstrated experience with a modern engineering tech stack (Airflow, AWS, Docker)
Experience working with a business intelligence tool like Tableau, PowerBI, Looker
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