Staff Analytics Engineer

Responsibilities

• Use SQL, Python, Snowflake, dbt, Airflow, and other systems in an agile development model to build and maintain data infrastructure for reporting, analysis, and automation.
• Perform data QA and develop automated testing procedures for Snowflake data models.
• Translate reporting, analysis, and automation requirements into data model requirements and specifications.
• Work with IT and other technical stakeholders to source data from key business systems and Snowflake databases.
• Architect flexible, performant data models that support a wide range of use cases while driving the organization towards single sources of truth.
• Provide input into data governance strategies and frameworks including permissions and security models, data lineage systems, and data definitions.
• Meet regularly with Accounting BI and technical leads to define requirements, formulate project plans, provide status updates, and perform user testing and QA.
• Build and maintain user-friendly documentation for data models and key metrics.
• Identify weaknesses in processes, data, and systems, and drive organizational improvements within the Analytics Engineering team.

Requirements

• 8+ years of experience working as an analytics, data, or BI engineer.
• Advanced SQL skills with experience standardizing queries and building data infrastructure involving large-scale relational datasets.
• Experience using Python to parse, structure, and transform data.
• Experience with MPP databases such as Snowflake, Redshift, BigQuery, or other relevant technologies.
• Ability to communicate effectively and efficiently with a wide range of stakeholders.
• Ability to prioritize and execute tasks in a high-pressure, constantly changing environment.
• Ability to think creatively to solve problems.
• Impulse for introducing structure and simplicity into vague, complex problems.
• Obsession for detail and quality.
• Ability to identify weaknesses in data and process, and willingness to drive improvement.
• Bias for action.

Nice-to-Haves

• Experience with ERP and Financial Planning tools.
• Experience using Python to parse, structure, and transform data (bonus for Streamlit specifically).
• Experience working with CI/CD pipelines.
• Experience leading or working within a scrum, sprint, or other agile framework.
• Past experience working in an accounting role, or directly supporting analysis and reporting for accounting stakeholders.