Senior Analytics Engineer

8+ years of experience within data and analytics
3+ years of experience working with dbt
3+ years of experience with Tableau, creating and managing data sources and dashboards
1+ year of experience administering a Tableau Server or Tableau Online installation
Proficiency in SQL, with strong knowledge of data manipulation, data modeling and query performance optimization, and the ability to manage large data sets and databases
Experience with modern databases and warehouses like Redshift, Snowflake, Postgres, MySQL, or Google BigQuery
Excellent problem-solving and quantitative skills, including the ability to identify root causes and recommend solutions
Meticulous attention to detail
Familiarity with git workflows
A proactive, solution-oriented mindset with a predisposition towards collaboration and communication

Partner with business stakeholders to establish and refine key metrics, creating and maintaining data sources and dashboards that empower stakeholders to make data-informed decisions
Establish standards for reporting in Tableau, drawing on experience to create intuitive and easy to use data visualizations appropriate for the data and business area
Lead the charge for making data discoverable by making documentation available and navigable for end users so they can self serve, and educate them on how to get the most out of Tableau
Develop and optimize data models for analytical use cases using dbt, leveraging tests and best practices to ensure accurate, scalable, and high-quality datasets
Serve as the architect for our dbt project: own and evolve the project’s architecture, design patterns, and best practices, ensuring consistency in data definitions and streamlined development
Design and implement Tableau Cloud data and workbook security model, and partner with IT to manage access, user roles, and permissions
Set up tests to ensure data quality and freshness, monitor daily job execution, and diagnose/fix issues within dbt flows, working with stakeholders to resolve root causes
Support maintenance and troubleshooting of ETL/ELT pipelines upstream of dbt that ingest, transform, and load data from various sources into the data warehouse (e.g., cloud storage, databases, APIs)

Strong perspective on analytics engineering development cycle, including data modeling, version control, documentation + testing, monitoring, and best practices for codebase development
Experience with Airflow or similar
Some Python experience and the ability to read a stack trace