People Analytics Data Engineer
Avalara Brasil
Job Overview
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Job Description
Overview
The People Analytics Data Engineer at Avalara Brasil works remotely in Brazil reporting to a US-based Manager to enable the HR team to make informed decisions by leveraging data. You will integrate and maintain people data across systems, working closely with HR and technical teams.
Key Responsibilities
- Design, build, and maintain scalable data pipelines using Snowflake, dbt, and Fivetran.
- Implement and optimize ELT processes ensuring high-quality, reliable data.
- Develop and maintain SQL queries, scripts, and documentation.
- Troubleshoot data issues while adhering to governance and privacy standards.
- Collaborate with HR stakeholders and engineering teams for seamless data integration.
What You Need to Succeed
- Experience as a Data Engineer or similar role with strong SQL skills.
- Proficiency with modern data stack tools such as Snowflake, dbt, Fivetran, and GitLab.
- Familiarity with ELT processes, data modeling, and data security techniques.
- Bachelor's degree in Computer Science, Information Technology, or related field.
- Bonus experience with Workday, ICIMS, Power BI, Python, and other analytics platforms.
About Avalara
At Avalara, an AI-first company, AI is embedded in workflows, decision-making, and products. As part of a billion-dollar business with leading cloud compliance technology, you will help drive efficiency and impact, delivering data-driven insights while maintaining a strong culture of diversity, equity, and inclusion.
Total Rewards & Benefits
Benefits include competitive compensation, paid time off, parental leave, bonuses, and comprehensive health & wellness coverage.
Key skills/competency
- Data Pipelines
- SQL
- Snowflake
- dbt
- Fivetran
- ELT
- Data Security
- People Analytics
- Data Modeling
- Automation
How to Get Hired at Avalara Brasil
- Research Avalara Brasil's culture: Study their mission, values, and recent news.
- Customize your resume: Emphasize data engineering and analytics skills.
- Prepare technical examples: Highlight successful data pipeline projects.
- Practice clear communication: Demonstrate collaboration with stakeholders.
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