Business Intelligence Analyst / Analytics Engineer

What You’ll Do

Data Modeling & Infrastructure (Analytics Engineering)

• Design and maintain clean, scalable data models (e.g., using dbt or similar tools)
• Transform raw data into well-structured datasets for analytics and reporting
• Partner with engineering to define data pipelines and improve data architecture
• Ensure data quality, testing, and documentation across datasets
• Build and maintain a single source of truth for key business metrics

Analytics & Business Intelligence

• Build dashboards and reporting for product, operations, and leadership
• Analyze complex datasets to identify trends and opportunities
• Translate ambiguous business problems into structured analysis
• Define and standardize core metrics (e.g., turnaround time, throughput, client performance)
• Support experimentation and product decision-making with data

Cross-Functional Impact

• Collaborate with engineering and stakeholders to improve data accessibility
• Enable teams to self-serve data through well-designed models and dashboards
• Act as a bridge between technical data systems and business needs

What We’re Looking For

• 3+ years of experience in BI, data analytics, or analytics engineering
• Strong SQL skills (advanced querying, joins, performance optimization)
• Experience building data models and working with transformation tools (e.g., dbt preferred)
• Experience with BI tools (Looker, Tableau, Power BI, etc.)
• Experience working in a startup or high-growth environment
• Strong understanding of data warehousing concepts
• Ability to own problems end-to-end (data → model → insight → impact)
• Strong communication skills across technical and non-technical audiences

Nice to Have

• Experience with modern data stack (dbt, Snowflake, BigQuery, Redshift)
• Familiarity with Python for data workflows
• Experience working with product or operational analytics
• Exposure to event tracking or analytics instrumentation
• Background in SaaS, fintech, or data-heavy industries

What Success Looks Like

• Build reliable, scalable data models used across the company
• Establish a trusted source of truth for key metrics
• Reduce time-to-insight for product and operations teams
• Deliver insights that directly improve efficiency, product performance, and growth
• Enable self-serve analytics across teams

Why This Role Matters (Difference vs BI Analyst)

A standard BI Analyst:

• Builds dashboards
• Answers questions

This role:

• Defines the data models behind those dashboards
• Owns data quality and metric definitions
• Builds infrastructure that scales with the company