Upside
Engineering Manager - Analytics Engineering
Upside, Washington, District of Columbia, us, 20022
About Upside
Upside transforms brick‑and‑mortar commerce with a platform that delivers higher cashback, measurable retailer profits, and sustainability initiatives.
About the Role You’ll lead the Analytics Engineering team that owns Upside’s core data platform, scaling ingestion, modeling, orchestration, and tooling to power company‑wide analytics and data‑driven decisions.
Responsibilities
Co‑create the vision and roadmap for Upside’s data platform, shaping strategy for data across the company.
Drive strategic data platform initiatives to improve reproducibility, reliability, and analytics enablement.
Define and track key platform health metrics, including pipeline reliability, SLA adherence, cost efficiency, and model deployment readiness.
Partner cross‑functionally with Product, Engineering, Data Science, and GTM stakeholders to ensure the data platform supports current and emerging business needs.
Represent Analytics Engineering in company‑wide planning forums, technical councils, and cross‑functional working groups.
Leadership Responsibilities
Create a safe, collaborative team environment.
Operate with a first‑team mindset.
Raise the bar by improving quality, performance, speed of execution, and engineering standards.
Grow talent through coaching, recognition, and skill development.
Set clarity and empower autonomy, ensuring expectations and direction are clearly articulated.
Team & Tools The team utilizes Snowflake, dbt, and Dagster, and is focused on building scalable, self‑service, and trustworthy workflows for reporting, analytics, and experimentation.
Ideal Qualifications
3+ years managing data, analytics, or ML engineering teams.
3+ years hands‑on experience building data products, pipelines, or ML systems.
Proficiency with Snowflake, dbt, and Dagster, and core concepts of modeling, orchestration, and data transformation.
Hands‑on experience with MLOps practices, such as model versioning, deployment pipelines, monitoring, and reproducibility.
Experience scaling teams, elevating systems, and bringing clarity to ambiguity.
Comfort designing and reviewing solutions in AWS environments.
Ability to communicate clearly across technical and non‑technical audiences.
Why You Should Apply
Opportunity to challenge the status quo and make data‑driven change.
Intersection of systems, storytelling, and experimentation.
Build resilient systems that scale with a continuous improvement mindset.
Champion quality upstream, encouraging early testing and validation.
Compensation & Benefits US base salary range $185,000 – $215,000 plus equity and benefits.
Benefits include:
Medical, dental, and vision coverage starting Day 1
Equity (ISOs)
401(k) program
Family planning programs and paid parental leave
Physical fitness and wellness memberships
Unlimited PTO, 10 paid federal holidays, and annual winter break
Flexible work environment and lunch reimbursement for in‑office employees
Employee Resource Groups, learning stipend, and transparent culture
Diversity & Inclusion Diversity drives innovation. Upside welcomes candidates from all backgrounds and does not discriminate based on protected characteristics. Accommodations for disabilities are available.
Location Hybrid role based in Austin, Chicago, DC, or NYC. In‑office attendance required on Monday, Tuesday, and Thursday.
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About the Role You’ll lead the Analytics Engineering team that owns Upside’s core data platform, scaling ingestion, modeling, orchestration, and tooling to power company‑wide analytics and data‑driven decisions.
Responsibilities
Co‑create the vision and roadmap for Upside’s data platform, shaping strategy for data across the company.
Drive strategic data platform initiatives to improve reproducibility, reliability, and analytics enablement.
Define and track key platform health metrics, including pipeline reliability, SLA adherence, cost efficiency, and model deployment readiness.
Partner cross‑functionally with Product, Engineering, Data Science, and GTM stakeholders to ensure the data platform supports current and emerging business needs.
Represent Analytics Engineering in company‑wide planning forums, technical councils, and cross‑functional working groups.
Leadership Responsibilities
Create a safe, collaborative team environment.
Operate with a first‑team mindset.
Raise the bar by improving quality, performance, speed of execution, and engineering standards.
Grow talent through coaching, recognition, and skill development.
Set clarity and empower autonomy, ensuring expectations and direction are clearly articulated.
Team & Tools The team utilizes Snowflake, dbt, and Dagster, and is focused on building scalable, self‑service, and trustworthy workflows for reporting, analytics, and experimentation.
Ideal Qualifications
3+ years managing data, analytics, or ML engineering teams.
3+ years hands‑on experience building data products, pipelines, or ML systems.
Proficiency with Snowflake, dbt, and Dagster, and core concepts of modeling, orchestration, and data transformation.
Hands‑on experience with MLOps practices, such as model versioning, deployment pipelines, monitoring, and reproducibility.
Experience scaling teams, elevating systems, and bringing clarity to ambiguity.
Comfort designing and reviewing solutions in AWS environments.
Ability to communicate clearly across technical and non‑technical audiences.
Why You Should Apply
Opportunity to challenge the status quo and make data‑driven change.
Intersection of systems, storytelling, and experimentation.
Build resilient systems that scale with a continuous improvement mindset.
Champion quality upstream, encouraging early testing and validation.
Compensation & Benefits US base salary range $185,000 – $215,000 plus equity and benefits.
Benefits include:
Medical, dental, and vision coverage starting Day 1
Equity (ISOs)
401(k) program
Family planning programs and paid parental leave
Physical fitness and wellness memberships
Unlimited PTO, 10 paid federal holidays, and annual winter break
Flexible work environment and lunch reimbursement for in‑office employees
Employee Resource Groups, learning stipend, and transparent culture
Diversity & Inclusion Diversity drives innovation. Upside welcomes candidates from all backgrounds and does not discriminate based on protected characteristics. Accommodations for disabilities are available.
Location Hybrid role based in Austin, Chicago, DC, or NYC. In‑office attendance required on Monday, Tuesday, and Thursday.
#J-18808-Ljbffr