# Analytics Engineer, Data Platform

**Company:** [Upside](https://hotfix.jobs/companies/upside)
**Location:** Washington, DC, New York, NY, Austin, TX, Chicago, IL
**Role:** Data Engineering
**Salary:** $149k – $180k/yr
**Experience:** 3+ years
**Skills:** SQL, Python, dbt, Snowflake, Dagster, Airflow, AWS, CI/CD, Data Modeling, Data Governance, Braze, Iterable, Segment, Machine Learning
**Posted:** 2026-09-03

> Own and evolve trusted data models for Marketing and Product use cases, from design and testing through monitoring and documentation. The role requires 3–5 years of data or analytics engineering experience, strong SQL and Python, dbt expertise, and Snowflake or comparable warehouse experience.

## Job Description

## Responsibilities
- Own a scoped domain of dbt models: design, build, test, ship, monitor, and document them.
- Turn ambiguous Marketing and Product requests into scoped, actionable work and communicate tradeoffs.
- Write design documents and break work into pieces teammates can pick up.
- Add monitoring and alerting so model issues are identified before stakeholders encounter them.
- Participate in the support rotation, debug failures, and prevent recurring issues.
- Create runbooks, schema documentation, and diagrams.
- Coach early-career engineers through code reviews and day-to-day collaboration.

## Requirements
- Approximately 3–5 years of data or analytics engineering experience, or comparable experience under another title.
- Strong SQL skills, including window functions, complex joins, and query-performance considerations.
- Experience owning dbt models in a version-controlled repository, including conventions, tests, CI, and maintenance.
- Proficiency with Python for orchestration, transformations, and testing.
- Ability to evaluate and explain data-modeling tradeoffs, including dimensional models versus consolidated tables.
- Ability to communicate technical decisions effectively to both technical and non-technical stakeholders.
- Experience with Snowflake or a comparable data warehouse.

## Nice to Have
- Marketing, growth, or lifecycle data experience, including events, attribution, experimentation, Braze, Iterable, or Segment.
- Experience with Dagster, Airflow, or another modern orchestrator.
- CI/CD for data, data governance, or cost-conscious warehouse design.
- Experience supporting machine-learning workflows, including feature development or monitoring model inputs.
- Experience making warehouse data usable by AI tooling through semantic layers, data contracts, or documentation.

## Compensation and Benefits
- Salary: $149,000–$180,000 annually.
- Medical, dental, and vision coverage starting on day one.
- Equity through ISOs.
- 401(k) program.
- Family planning programs and paid parental leave.
- Fitness and wellness memberships.
- Emotional and mental health support programs.
- Unlimited PTO, paid federal holidays, and an annual week-long winter break.
- Flexible work environment.
- Lunch reimbursement for in-office employees.
- Employee Resource Groups.
- Learning and development stipend.

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