Data Platform Analytics Engineer: Build trusted models

Upside; Columbia, Northern (IL, KY); Hybrid; USD 110,000 - 170,000; Full time

Benefits offered by this job

Medical benefits

Equity

401(k) plan

Parental leave

Flexible schedule

Lunch reimbursement

Learning stipend

Transparent culture

Winter break

Job summary

Upside is seeking a data/analytics engineer to own a scoped domain of dbt models, designing, building, testing, and monitoring them with a clear structure. You’ll work closely with Marketing, Data, and MarTech to turn ambiguous questions into concrete, trustworthy data solutions.

You’ll collaborate with Snowflake, dbt, Dagster, and AWS in a small six-person team, writing design docs, and coaching junior engineers while improving performance and data quality across the lifecycle.

Qualifications

• 3-5 years in data or analytics engineering.
• Fluent in SQL with window functions and complex joins.
• Owned dbt models in a version-controlled repo.
• Python for orchestration, transformations, and tests.
• Explain technical decisions to marketers and engineers.
• Experience with Snowflake or a comparable warehouse.

Responsibilities

• Own a scoped domain of dbt models: design, build, test, ship, monitor.
• Turn ambiguous asks into scoped work and discuss tradeoffs.
• Write a design doc and break work into components.
• Add monitoring and alerting to models to catch issues.
• Sit on our support rotation and debug issues.
• Leave runbooks, schema docs, and diagrams for continuity.
• Coach engineers on code reviews and day-to-day work.

Skills

SQL

dbt

Python

Snowflake

Data modeling

Performance tuning

Tools

Snowflake

dbt

Dagster

AWS

Job description

Upside is seeking a data/analytics engineer to own a scoped domain of dbt models, designing, building, testing, and monitoring them with a clear structure. You’ll work closely with Marketing, Data, and MarTech to turn ambiguous questions into concrete, trustworthy data solutions.

You’ll collaborate with Snowflake, dbt, Dagster, and AWS in a small six-person team, writing design docs, and coaching junior engineers while improving performance and data quality across the lifecycle.