Collaborate with data engineering, analytics, product, and marketing teams to design and implement reliable, scalable data models and transformation pipelines.
Develop and maintain dbt models, macros, and documentation that ensure data accuracy, reusability, and clarity across the organization.
Partner with business stakeholders to translate analytical needs into well-structured datasets that support reporting and self-service analytics.
Support and uphold best practices for data modeling, testing, version control, and documentation across analytics workflows.
Proactively identify and address issues in data quality, model performance, and pipeline efficiency.
Contribute to the standardization of metrics, definitions, and semantic layers to ensure consistent reporting across business units.
Participate in code reviews and knowledge-sharing to continuously improve team processes and data craftsmanship.
Stay current with modern data tools, frameworks, and best practices to help evolve our analytics engineering stack.

5+ years of experience in analytics engineering, data modeling, or business intelligence roles.
Strong proficiency in SQL and experience with cloud-based data platforms (e.g., Snowflake).
Hands-on experience with dbt (modular SQL, testing, documentation, Jinja).
Familiarity with data ingestion tools (e.g., Fivetran) and version control systems (e.g., Git).
Strong understanding of data governance, testing, and lineage principles.
Ability to communicate data concepts effectively to both technical and non-technical audiences.
Attention to detail, curiosity, and a proactive approach to problem-solving.
Comprehension of data contract and semantic layer design concepts.

Senior Analytics Engineer

Key skills