Hiring BI Engineers: The Complete Guide

# BI Engineer

**Location:** Chicago, IL (Hybrid) · **Employment Type:** Full-time · **Level:** Mid-Senior

## About [Company]

[Company] is building a data-driven culture where every team can access the insights they need. Our analytics platform serves 500+ internal users across sales, marketing, operations, and finance. We process $2B+ in transactions and need clear visibility into performance.

We're a team of 65 engineers, including 4 data engineers and 2 BI specialists. We're Series B funded ($40M) and analytics is central to how we operate—decisions are made with data, not gut feelings.

**Why join [Company]?**

- Build dashboards that directly influence $2B+ in business decisions
- Shape analytics strategy for a growing organization
- Work with modern tools (Looker, dbt, Snowflake)
- Competitive compensation with meaningful equity
- Collaborative culture where BI is valued, not an afterthought

## The Role

We're looking for a BI Engineer to build and maintain the analytics platform that powers decision-making across [Company]. You'll work directly with stakeholders to understand their needs, design intuitive dashboards, and enable self-service analytics.

The ideal candidate loves making data accessible. You care about user adoption, not just building dashboards. You're comfortable working with business stakeholders and can translate vague requests into precise specifications. You believe dashboards should be self-explanatory and require minimal training.

## What You'll Work On

### First 30 Days
- Understand our data model, semantic layer, and existing dashboards
- Meet with key stakeholders across Sales, Marketing, Operations, Finance
- Ship your first dashboard improvement
- Review our metrics definitions and documentation

### First 90 Days
- Own a major dashboard project end-to-end (requirements → design → build → adoption)
- Improve self-service capabilities—reduce ad-hoc requests by 30%
- Document key metrics and business logic
- Establish dashboard design standards

### First Year
- Lead BI technical direction and tool selection
- Achieve 80%+ dashboard adoption across key users
- Build self-service training program
- Reduce time-to-insight from days to hours for common questions

## Responsibilities

**Dashboard Development (50%)**
- Build dashboards and reports for business stakeholders
- Define metrics and business logic in our semantic layer (LookML)
- Optimize dashboard performance for large datasets
- Design intuitive UX that requires minimal training

**Self-Service & Documentation (30%)**
- Enable self-service analytics for business teams
- Document data sources, metrics, and methodology
- Train stakeholders on self-service capabilities
- Build and maintain a data dictionary

**Collaboration & Strategy (20%)**
- Gather requirements and translate to technical specifications
- Collaborate with data engineering on data model improvements
- Advise on analytics strategy and tool selection
- Participate in data governance discussions

## Required Skills and Qualifications

**Technical Skills**
- 3+ years experience in BI, analytics, or data engineering
- Expert SQL skills (CTEs, window functions, optimization)
- Proficiency with BI tools—we use Looker, but Tableau/Power BI experience transfers
- Strong data visualization skills and design sensibility
- Experience with dimensional modeling and data warehouses
- Familiarity with dbt or similar transformation tools

**Soft Skills**
- Excellent communication with non-technical stakeholders
- Ability to translate vague requests into precise specifications
- User-focused mindset—you measure success by adoption, not dashboard count
- Patience and empathy—stakeholders don't think in SQL

## Nice to Have

- Looker (LookML) experience strongly preferred
- dbt proficiency
- Snowflake experience
- Python for data manipulation
- Experience building self-service analytics programs

## Tech Stack

**BI Layer:** Looker (LookML semantic layer)
**Data Warehouse:** Snowflake (multi-TB, 5+ years of history)
**Transformation:** dbt (150+ models)
**Orchestration:** Airflow
**Documentation:** Notion, custom data dictionary

## Compensation and Benefits

**Salary:** $120,000 - $165,000 (based on experience)
**Equity:** 0.03% - 0.10% (standard 4-year vesting with 1-year cliff)
**Bonus:** 10-15% annual target

**Benefits:**
- Health, dental, vision (100% covered for employee)
- 401(k) with 4% match
- Unlimited PTO (average taken: 4 weeks)
- $1,500/year learning budget
- Work from home flexibility (2-3 days/week in office)

## Interview Process

1. **Recruiter Screen** (30 min) - Background and mutual fit
2. **Technical Screen** (60 min) - SQL assessment and BI fundamentals
3. **Take-Home** (2-3 hours) - Design a dashboard for a business scenario
4. **Onsite** (3.5 hours, can be virtual)
   - Portfolio Review (60 min) - Deep dive into your take-home and past work
   - Stakeholder Simulation (45 min) - Requirements gathering with "stakeholder"
   - Technical Deep Dive (45 min) - SQL, data modeling, and optimization
   - Culture Fit (45 min) - Team fit and working style
5. **Offer** - Within 48 hours of final interview

We aim to complete the process in 2 weeks.