Engineering Manager - Data Engineering

About the Role We’re looking for an Engineering Manager to lead our Data Engineering team, the owners of Upside’s core data platform, whose responsibilities include ingestion, modeling, orchestration, and tooling to power analytics and data‑driven decisions across the company. The Manager will combine technical acumen with people‑first leadership to scale our platform, foster engineering growth, and drive data accessibility and trust across internal teams. They will also guide the evolution of MLOps practices to support the development, deployment, and monitoring of machine learning models used in personalization and optimization features. Leadership Responsibilities Co‑create and drive the vision and roadmap for Upside’s data platform, shaping the strategy for data across Upside in alignment with company goals. Ensure the data stack, which includes Snowflake, dbt, and Dagster, enables scalable, self‑service, and trustworthy workflows for reporting, analytics, and experimentation. Drive strategic data platform initiatives that improve reproducibility, reliability, and analytics enablement, such as modernizing legacy infrastructure, implementing tools like Snowflake Semantic Views and Cortex, and transforming 3rd‑party data into trusted, production‑ready assets. 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. Why You Should Apply You aren’t afraid to challenge the status quo when it makes the team and business better, and you learn from those around you while using data to advocate for informed change. You thrive at the intersection of systems and storytelling, building robust solutions and communicating their purpose, impact, and rationale so teams can experiment, iterate, and act confidently. You care about building resilient systems that scale, bringing a mindset of continuous improvement and knowing when to invest in observability, automation, or new infrastructure to reduce toil and improve outcomes for the team and end users. You believe that pulling quality upstream starts with engineering, championing best practices and encouraging early testing and validation to build a culture of quality from the ground up. Ideal Qualifications Have 3+ years of experience managing data, analytics, or ML engineering teams, and at least 3+ years of hands‑on experience as an individual contributor building data products, pipelines, or ML systems. Are proficient with modern data platforms and tooling, including Snowflake, dbt, and Dagster, and are fluent in core concepts like modeling, orchestration, and data transformation. Have hands‑on experience or deep familiarity with MLOps practices such as model versioning, deployment pipelines, monitoring, and reproducibility. Thrive in environments where you’re asked to scale teams, elevate systems, and bring clarity to ambiguity. Are comfortable designing and reviewing solutions in AWS environments, and make thoughtful tradeoffs to balance performance, cost, and maintainability. Are eager to integrate generative AI tools into development workflows to accelerate delivery and improve the developer experience. Communicate clearly across technical and non‑technical audiences, and can advocate effectively for platform investments that support long‑term business value. Engineering Culture Our engineering leaders are expected to coach their teams and make thoughtful, impactful technical decisions. Managers typically focus on a team of about 8 direct reports, while more senior managers may operate across two teams. Staff composition combines full‑time and contract employees for a mix of continuity and flexibility. Location This hybrid role is based in Austin, Chicago, Washington, DC, or New York City. In‑office attendance is required on Monday, Tuesday, and Thursday, with potential adjustments based on project needs and policy changes. Compensation The US base salary range for this full‑time position is $185,000 – $215,000, plus equity and benefits. Final starting pay will be determined based on job‑related skills, experience, qualifications, work location, and market conditions. Benefits Medical, dental, and vision coverage starting on Day 1 Equity (ISOs) 401(k) program Family planning programs + paid parental leave Physical fitness and wellness memberships Emotional and mental health support programs Unlimited PTO, 10 paid federal holidays, and a week‑long winter break Flexible work environment Lunch reimbursement for in‑office employees Employee Resource Groups Learning and Development stipend Transparent culture Diversity and Inclusion Diversity drives innovation, and our differences make us stronger. We’re passionate about building a workplace that represents a variety of backgrounds, skills, and perspectives, and we do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Everyone is welcome here. If there’s anything we can do to support a disability or special need during your application or interview process, please email View email address on click.appcast.io. #J-18808-Ljbffr Upside