Responsibilities

• Design and develop core data models to enhance analytical efficiency and generate rapid, reliable insights.
• Define and implement data modeling standards and best practices using tools like dbt.
• Improve data team productivity by optimizing tooling, automating workflows, and streamlining data processes.
• Select and manage analytics tooling, balancing build vs. buy decisions and vendor relationships.
• Collaborate with Data Scientists to translate business requirements into effective data solutions.
• Develop and maintain key dashboards and reports to track business performance and drive strategic decisions.
• Lead data governance initiatives, ensuring security, compliance, and data quality standards are consistently met.

Qualifications & Requirements

Minimum Requirements:

• 4+ years of experience as an Analytics Engineer, Data Engineer, Data Scientist, or a closely related role.
• Expertise in SQL, including complex queries, performance optimization, and data transformation.
• Strong background in data modeling, including dimensional modeling and analytics engineering best practices.
• Experience in dashboard development and data visualization using BI tools such as Looker, Mode, Hex, or similar.
• Previous experience in a fast-paced, high-growth environment with the ability to adapt and scale analytics solutions.
• Self-starter mindset, capable of independently driving projects from concept to execution with minimal supervision.

Bonus Skills

• Experience with dbt, including building and maintaining analytics workflows.
• Proficiency in Python for data processing and automation.
• Experience with Snowflake administration, performance tuning, and optimization.
• Familiarity with Databricks and cloud-based data platforms.
• Previous experience as an early-stage Analytics Engineer in a high-growth startup or consulting environment.