Intermediate Analytics Developer
New
J
JobgetherAI-focused SaaS
Based in the United States, East Coast U.S. office hoursContractMiddle
Salary not disclosed
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Job Details
- Languages
- English (at least a strong B2 level)
- Experience
- 3+ years
- Required Skills
- PythonSQLData engineeringData modelingLookerGenerative AI
Requirements
- Bachelor’s degree or equivalent experience in a quantitative field such as statistics, mathematics, computer science, engineering, or economics.
- 3+ years of experience in data analysis, analytics development, or a similar data-focused role.
- Strong SQL skills with hands-on experience using Google BigQuery and Looker.
- Practical Python experience for data-related tasks, including scripting and pipeline development.
- Working knowledge of data warehousing concepts and scalable data products.
- Solid statistical foundation, including familiarity with t-tests and linear regression.
- Familiarity with Generative AI tools and large language models for code generation, cleaning, and analysis.
- Strong ability to communicate data concepts and technical issues to diverse audiences.
- Strong product and business judgment.
- Strong English communication skills (minimum B2 level).
- Ability to work independently in a remote environment.
Responsibilities
- Build and maintain user-facing reports and analytics products to help customers understand workforce data.
- Develop and maintain data models and pipelines in Google BigQuery using partitioning and clustering.
- Apply statistical methods to analyze data and support informed product decisions.
- Collaborate with Product Managers, Developers, and Designers to conduct feature analyses and deliver actionable insights.
- Review data schemas for new product features to ensure support for analytics and BI requirements.
- Participate in pull request reviews and provide feedback on code quality.
- Troubleshoot issues across the analytics stack from data ingestion to the semantic layer.
- Work with AI agent tools to support workflow automation and improve data experiences.
- Contribute to team knowledge base and document best practices.
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