Data Platform Analytics Engineer — Build & Optimize Data Models

Upside; City of Syracuse, City of Auburn (NY, NY); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Medical/dental/vision

Equity (ISOs)

401(k)

Parental leave

Wellness stipend

Unlimited PTO

Flexible work

Lunch reimbursement

Learning & development

Job summary

Upside is seeking a data analytics engineer to own and evolve a set of dbt models, turning complex data questions from Marketing and Product into concrete, scalable solutions. You’ll work closely with Marketing, Data, and MarTech to turn messy questions into reliable, well-documented data products.

The role emphasizes SQL proficiency, dbt ownership, and Python-driven data transformations, with opportunities to mentor junior engineers and shape data strategy across the platform.

Qualifications

• 3–5 years in data or analytics engineering or equivalent work.
• Fluent in SQL with strong window functions and joins; performance-minded.
• Experience owning dbt models in a version-controlled repo with tests.
• Proficient in Python for orchestrations, transformations, and tests.
• Ability to explain technical decisions to marketers and engineers.

Responsibilities

• Own a scoped domain of dbt models: design, build, test, ship, and monitor.
• Turn ambiguous asks from Marketing and Product into scoped work with tradeoffs.
• Write design docs for owned features and break work into reusable pieces.
• Add monitoring and alerting to models to catch issues early.
• Contribute to runbooks, schema docs, and diagrams for maintainability.
• Mentor engineers on the team through code reviews and daily work.

Skills

SQL

Window functions

dbt

Python

Data modeling

Tools

Snowflake

Dagster

Airflow

dbt

Job description

Upside is seeking a data analytics engineer to own and evolve a set of dbt models, turning complex data questions from Marketing and Product into concrete, scalable solutions. You’ll work closely with Marketing, Data, and MarTech to turn messy questions into reliable, well-documented data products.

The role emphasizes SQL proficiency, dbt ownership, and Python-driven data transformations, with opportunities to mentor junior engineers and shape data strategy across the platform.