The company is looking to bridge data engineering, business intelligence, and analytics by hiring an Analytics Engineer to own the full data lifecycle, from ingestion and transformation to dashboard building and enabling business users.
Requirements
- Proficiency in SQL for data modeling, transformations, and performance optimization.
- Proficiency in Python for automation, data manipulation, and analytics workflows.
- Experience working with APIs for data ingestion, integration, and automation.
- Familiarity with medallion/lakehouse architectures and developing transformation pipelines (bronze ? silver ? gold).
- Strong skills in BI and data visualization tools (e.g., Power BI, Tableau, Domo, Looker, or equivalent).
- Experience with version control (e.g., Git) and modern data development practices.
- Experience administering BI platforms, including governance, permissions, and content management.
Responsibilities
- Design, build, and maintain BI dashboards and visualizations that support decision-making.
- Build and manage data pipelines and transformations across a medallion architecture.
- Apply business logic, validation, and documentation to ensure accuracy, consistency, and trusted datasets.
- Monitor and troubleshoot data quality and pipeline issues, implementing automation where possible.
- Administer and govern the BI platform, including permissions, content management, and standards.
- Partner with business stakeholders to understand requirements and deliver actionable data products.
- Stay current on tools and methods, recommending improvements to platforms, processes, and governance.
Other
- Bachelor’s degree in computer science, data science, information systems, or a related field; or equivalent professional experience.
- 3–5 years of experience in analytics engineering, data engineering, BI development, or a closely related role.
- Experience working cross-functionally with business teams to translate requirements into data products.
- Ability to communicate technical concepts clearly to non-technical audiences.
- Experience training and enabling business users in data literacy, visualization techniques, and self-service analytics.
